{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false, "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "import pandas as pd" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false, "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
地区机组类型参数分类冷却方式锅炉类型机组容量入炉煤低位热值_new燃煤挥发份Var_new燃煤灰份Aar_new服役时长CO2_em_air
0上海纯凝式亚临界水冷煤粉320.019595.9829.0810.2220.00.266602
1上海纯凝式亚临界水冷煤粉320.019971.7829.0810.2221.00.260793
2上海纯凝式亚临界水冷煤粉320.019993.0129.0810.2219.00.269131
3上海纯凝式亚临界水冷煤粉320.020328.2129.0810.2221.00.268076
4上海纯凝式亚临界水冷煤粉600.020591.0027.7911.0015.00.254074
\n", "
" ], "text/plain": [ " 地区 机组类型 参数分类 冷却方式 锅炉类型 机组容量 入炉煤低位热值_new 燃煤挥发份Var_new 燃煤灰份Aar_new \\\n", "0 上海 纯凝式 亚临界 水冷 煤粉 320.0 19595.98 29.08 10.22 \n", "1 上海 纯凝式 亚临界 水冷 煤粉 320.0 19971.78 29.08 10.22 \n", "2 上海 纯凝式 亚临界 水冷 煤粉 320.0 19993.01 29.08 10.22 \n", "3 上海 纯凝式 亚临界 水冷 煤粉 320.0 20328.21 29.08 10.22 \n", "4 上海 纯凝式 亚临界 水冷 煤粉 600.0 20591.00 27.79 11.00 \n", "\n", " 服役时长 CO2_em_air \n", "0 20.0 0.266602 \n", "1 21.0 0.260793 \n", "2 19.0 0.269131 \n", "3 21.0 0.268076 \n", "4 15.0 0.254074 " ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data = pd.read_csv('./data/train_data85.csv')\n", "data.head()" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false, "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "text/plain": [ "['地区',\n", " '机组类型',\n", " '参数分类',\n", " '冷却方式',\n", " '锅炉类型',\n", " '机组容量',\n", " '入炉煤低位热值_new',\n", " '燃煤挥发份Var_new',\n", " '燃煤灰份Aar_new']" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "feature_cols = [x for x in data.columns if x!='CO2_em_air' and x != '服役时长']\n", "feature_cols" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false, "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "num_cols = ['机组容量', '入炉煤低位热值_new', '燃煤挥发份Var_new', '燃煤灰份Aar_new']\n", "obj_cols = [x for x in feature_cols if x not in num_cols]" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "import numpy as np" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "for col in num_cols:\n", " data[col] = np.log1p(data[col])\n", " data[col] = (data[col] - data[col].min()) / (data[col].max() - data[col].min())" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "use_data = pd.get_dummies(data, columns=obj_cols)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "for col in use_data.columns:\n", " use_data[col] = use_data[col].astype('float32')\n", "feature_cols = [x for x in use_data.columns if x != 'CO2_em_air']" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": false, "pycharm": { "name": "#%%\n" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "2023-02-15 15:27:24.563456: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n" ] } ], "source": [ "import tensorflow as tf\n", "from tensorflow import keras\n", "from tensorflow.keras import layers\n", "from tensorflow.keras import Model" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false, "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "class TransformerBlock(layers.Layer):\n", " def __init__(self, embed_dim, num_heads, ff_dim, rate=0.1):\n", " super().__init__()\n", " self.att = layers.MultiHeadAttention(num_heads=num_heads, key_dim=embed_dim)\n", " self.ffn = keras.Sequential(\n", " [layers.Dense(ff_dim, activation=\"relu\"), layers.Dense(embed_dim),]\n", " )\n", " self.layernorm1 = layers.LayerNormalization(epsilon=1e-6)\n", " self.layernorm2 = layers.LayerNormalization(epsilon=1e-6)\n", " self.dropout1 = layers.Dropout(rate)\n", " self.dropout2 = layers.Dropout(rate)\n", "\n", " def call(self, inputs, training):\n", " attn_output = self.att(inputs, inputs)\n", " attn_output = self.dropout1(attn_output, training=training)\n", " out1 = self.layernorm1(inputs + attn_output)\n", " ffn_output = self.ffn(out1)\n", " ffn_output = self.dropout2(ffn_output, training=training)\n", " return self.layernorm2(out1 + ffn_output)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false, "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "def build_model(num_heads, ff_dim):\n", " inputs = layers.Input(shape=(1,len(feature_cols)), name='input')\n", " x = layers.Conv1D(filters=64, kernel_size=1, activation='relu')(inputs)\n", " lstm_out = layers.Bidirectional(layers.LSTM(units=64, return_sequences=True))(x)\n", " lstm_out = layers.Dense(128, activation='relu')(lstm_out)\n", " transformer_block = TransformerBlock(128, num_heads, ff_dim)\n", " x = transformer_block(lstm_out)\n", " x = layers.GlobalAveragePooling1D()(x)\n", " x = layers.Dropout(0.1)(x)\n", " x = layers.Dense(32, activation=\"relu\")(x)\n", " x = layers.Dropout(0.1)(x)\n", " out = layers.Dense(1, name='out', activation=\"sigmoid\")(x)\n", "\n", " model = Model(inputs=[inputs], outputs=out)\n", " model.summary()\n", " return model" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": false, "pycharm": { "name": "#%%\n" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "2023-02-15 15:27:25.855423: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcuda.so.1\n", "2023-02-15 15:27:25.914976: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1733] Found device 0 with properties: \n", "pciBusID: 0000:35:00.0 name: NVIDIA A100-PCIE-40GB computeCapability: 8.0\n", "coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.41GiB deviceMemoryBandwidth: 1.41TiB/s\n", "2023-02-15 15:27:25.916491: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1733] Found device 1 with properties: \n", "pciBusID: 0000:9c:00.0 name: NVIDIA A100-PCIE-40GB computeCapability: 8.0\n", "coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.41GiB deviceMemoryBandwidth: 1.41TiB/s\n", "2023-02-15 15:27:25.916513: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", "2023-02-15 15:27:25.919898: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcublas.so.11\n", "2023-02-15 15:27:25.919954: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcublasLt.so.11\n", "2023-02-15 15:27:25.921620: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcufft.so.10\n", "2023-02-15 15:27:25.921895: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcurand.so.10\n", "2023-02-15 15:27:25.922926: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcusolver.so.11\n", "2023-02-15 15:27:25.923798: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcusparse.so.11\n", "2023-02-15 15:27:25.923919: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudnn.so.8\n", "2023-02-15 15:27:25.930727: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1871] Adding visible gpu devices: 0, 1\n", "2023-02-15 15:27:25.931098: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 AVX512F FMA\n", "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n", "2023-02-15 15:27:26.405499: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1733] Found device 0 with properties: \n", "pciBusID: 0000:35:00.0 name: NVIDIA A100-PCIE-40GB computeCapability: 8.0\n", "coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.41GiB deviceMemoryBandwidth: 1.41TiB/s\n", "2023-02-15 15:27:26.406851: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1733] Found device 1 with properties: \n", "pciBusID: 0000:9c:00.0 name: NVIDIA A100-PCIE-40GB computeCapability: 8.0\n", "coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.41GiB deviceMemoryBandwidth: 1.41TiB/s\n", "2023-02-15 15:27:26.413344: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1871] Adding visible gpu devices: 0, 1\n", "2023-02-15 15:27:26.413398: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", "2023-02-15 15:27:27.737158: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1258] Device interconnect StreamExecutor with strength 1 edge matrix:\n", "2023-02-15 15:27:27.737201: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1264] 0 1 \n", "2023-02-15 15:27:27.737207: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1277] 0: N Y \n", "2023-02-15 15:27:27.737211: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1277] 1: Y N \n", "2023-02-15 15:27:27.743435: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1418] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 7626 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-PCIE-40GB, pci bus id: 0000:35:00.0, compute capability: 8.0)\n", "2023-02-15 15:27:27.745129: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1418] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:1 with 5 MB memory) -> physical GPU (device: 1, name: NVIDIA A100-PCIE-40GB, pci bus id: 0000:9c:00.0, compute capability: 8.0)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Model: \"model\"\n", "_________________________________________________________________\n", "Layer (type) Output Shape Param # \n", "=================================================================\n", "input (InputLayer) [(None, 1, 44)] 0 \n", "_________________________________________________________________\n", "conv1d (Conv1D) (None, 1, 64) 2880 \n", "_________________________________________________________________\n", "bidirectional (Bidirectional (None, 1, 128) 66048 \n", "_________________________________________________________________\n", "dense (Dense) (None, 1, 128) 16512 \n", "_________________________________________________________________\n", "transformer_block (Transform (None, 1, 128) 202640 \n", "_________________________________________________________________\n", "global_average_pooling1d (Gl (None, 128) 0 \n", "_________________________________________________________________\n", "dropout_2 (Dropout) (None, 128) 0 \n", "_________________________________________________________________\n", "dense_3 (Dense) (None, 32) 4128 \n", "_________________________________________________________________\n", "dropout_3 (Dropout) (None, 32) 0 \n", "_________________________________________________________________\n", "out (Dense) (None, 1) 33 \n", "=================================================================\n", "Total params: 292,241\n", "Trainable params: 292,241\n", "Non-trainable params: 0\n", "_________________________________________________________________\n" ] } ], "source": [ "model = build_model(3, 16)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": false, "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "from sklearn.model_selection import train_test_split" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "from sklearn.model_selection import KFold\n", "from sklearn.metrics import mean_absolute_error, mean_squared_error, mean_absolute_percentage_error, r2_score" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "kf = KFold(n_splits=10, shuffle=True, random_state=666)" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['机组容量',\n", " '入炉煤低位热值_new',\n", " '燃煤挥发份Var_new',\n", " '燃煤灰份Aar_new',\n", " '服役时长',\n", " '地区_上海',\n", " '地区_云南',\n", " '地区_内蒙',\n", " '地区_北京',\n", " '地区_吉林',\n", " '地区_四川',\n", " '地区_天津',\n", " '地区_宁夏',\n", " '地区_安徽',\n", " '地区_山东',\n", " '地区_山西',\n", " '地区_广东',\n", " '地区_广西',\n", " '地区_新疆',\n", " '地区_江苏',\n", " '地区_江西',\n", " '地区_河北',\n", " '地区_河南',\n", " '地区_浙江',\n", " '地区_海南',\n", " '地区_湖北',\n", " '地区_湖南',\n", " '地区_甘肃',\n", " '地区_福建',\n", " '地区_贵州',\n", " '地区_辽宁',\n", " '地区_重庆',\n", " '地区_陕西',\n", " '地区_黑龙江',\n", " '机组类型_供热式',\n", " '机组类型_纯凝式',\n", " '参数分类_亚临界',\n", " '参数分类_超临界',\n", " '参数分类_超超临界',\n", " '参数分类_超高压',\n", " '冷却方式_水冷',\n", " '冷却方式_直接空冷',\n", " '冷却方式_间接空冷',\n", " '锅炉类型_煤粉']" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "feature_cols" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "from tensorflow.keras import optimizers" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "opt = optimizers.Adam(learning_rate=5e-5)" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "2023-02-15 15:27:29.091509: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:176] None of the MLIR Optimization Passes are enabled (registered 2)\n", "2023-02-15 15:27:29.110380: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2200000000 Hz\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 1/100\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2023-02-15 15:27:32.312182: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudnn.so.8\n", "2023-02-15 15:27:33.451542: I tensorflow/stream_executor/cuda/cuda_dnn.cc:359] Loaded cuDNN version 8401\n", "2023-02-15 15:27:34.663250: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcublas.so.11\n", "2023-02-15 15:27:34.663722: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcublasLt.so.11\n", "Could not load symbol cublasGetSmCountTarget from libcublas.so.11. Error: /usr/local/cuda-11.2/lib64/libcublas.so.11: undefined symbol: cublasGetSmCountTarget\n", "2023-02-15 15:27:34.853189: I tensorflow/stream_executor/cuda/cuda_blas.cc:1838] TensorFloat-32 will be used for the matrix multiplication. This will only be logged once.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "17/17 [==============================] - 7s 56ms/step - loss: 0.0865 - mae: 0.0865 - val_loss: 0.0356 - val_mae: 0.0356\n", "Epoch 2/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0695 - mae: 0.0695 - val_loss: 0.0307 - val_mae: 0.0307\n", "Epoch 3/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0625 - mae: 0.0625 - val_loss: 0.0269 - val_mae: 0.0269\n", "Epoch 4/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0518 - mae: 0.0518 - val_loss: 0.0256 - val_mae: 0.0256\n", "Epoch 5/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0487 - mae: 0.0487 - val_loss: 0.0224 - val_mae: 0.0224\n", "Epoch 6/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0450 - mae: 0.0450 - val_loss: 0.0199 - val_mae: 0.0199\n", "Epoch 7/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0437 - mae: 0.0437 - val_loss: 0.0195 - val_mae: 0.0195\n", "Epoch 8/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0435 - mae: 0.0435 - val_loss: 0.0192 - val_mae: 0.0192\n", "Epoch 9/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0401 - mae: 0.0401 - val_loss: 0.0178 - val_mae: 0.0178\n", "Epoch 10/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0412 - mae: 0.0412 - val_loss: 0.0175 - val_mae: 0.0175\n", "Epoch 11/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0375 - mae: 0.0375 - val_loss: 0.0160 - val_mae: 0.0160\n", "Epoch 12/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0393 - mae: 0.0393 - val_loss: 0.0157 - val_mae: 0.0157\n", "Epoch 13/100\n", "17/17 [==============================] - 0s 8ms/step - loss: 0.0384 - mae: 0.0384 - val_loss: 0.0133 - val_mae: 0.0133\n", "Epoch 14/100\n", "17/17 [==============================] - 0s 8ms/step - loss: 0.0366 - mae: 0.0366 - val_loss: 0.0184 - val_mae: 0.0184\n", "Epoch 15/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0365 - mae: 0.0365 - val_loss: 0.0138 - val_mae: 0.0138\n", "Epoch 16/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0376 - mae: 0.0376 - val_loss: 0.0151 - val_mae: 0.0151\n", "Epoch 17/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0379 - mae: 0.0379 - val_loss: 0.0143 - val_mae: 0.0143\n", "Epoch 18/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0358 - mae: 0.0358 - val_loss: 0.0144 - val_mae: 0.0144\n", "Epoch 19/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0374 - mae: 0.0374 - val_loss: 0.0149 - val_mae: 0.0149\n", "Epoch 20/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0356 - mae: 0.0356 - val_loss: 0.0136 - val_mae: 0.0136\n", "Epoch 21/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0351 - mae: 0.0351 - val_loss: 0.0142 - val_mae: 0.0142\n", "Epoch 22/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0357 - mae: 0.0357 - val_loss: 0.0188 - val_mae: 0.0188\n", "Epoch 23/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0374 - mae: 0.0374 - val_loss: 0.0146 - val_mae: 0.0146\n", "Epoch 24/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0348 - mae: 0.0348 - val_loss: 0.0157 - val_mae: 0.0157\n", "Epoch 25/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0348 - mae: 0.0348 - val_loss: 0.0157 - val_mae: 0.0157\n", "Epoch 26/100\n", "17/17 [==============================] - 0s 18ms/step - loss: 0.0351 - mae: 0.0351 - val_loss: 0.0147 - val_mae: 0.0147\n", "Epoch 27/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0355 - mae: 0.0355 - val_loss: 0.0125 - val_mae: 0.0125\n", "Epoch 28/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0321 - mae: 0.0321 - val_loss: 0.0123 - val_mae: 0.0123\n", "Epoch 29/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0324 - mae: 0.0324 - val_loss: 0.0133 - val_mae: 0.0133\n", "Epoch 30/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0336 - mae: 0.0336 - val_loss: 0.0173 - val_mae: 0.0173\n", "Epoch 31/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0339 - mae: 0.0339 - val_loss: 0.0127 - val_mae: 0.0127\n", "Epoch 32/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0332 - mae: 0.0332 - val_loss: 0.0136 - val_mae: 0.0136\n", "Epoch 33/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0333 - mae: 0.0333 - val_loss: 0.0132 - val_mae: 0.0132\n", "Epoch 34/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0312 - mae: 0.0312 - val_loss: 0.0147 - val_mae: 0.0147\n", "Epoch 35/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0337 - mae: 0.0337 - val_loss: 0.0133 - val_mae: 0.0133\n", "Epoch 36/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0306 - mae: 0.0306 - val_loss: 0.0128 - val_mae: 0.0128\n", "Epoch 37/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0324 - mae: 0.0324 - val_loss: 0.0160 - val_mae: 0.0160\n", "Epoch 38/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0320 - mae: 0.0320 - val_loss: 0.0131 - val_mae: 0.0131\n", "Epoch 39/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0312 - mae: 0.0312 - val_loss: 0.0127 - val_mae: 0.0127\n", "Epoch 40/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0302 - mae: 0.0302 - val_loss: 0.0151 - val_mae: 0.0151\n", "Epoch 41/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0316 - mae: 0.0316 - val_loss: 0.0131 - val_mae: 0.0131\n", "Epoch 42/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0334 - mae: 0.0334 - val_loss: 0.0179 - val_mae: 0.0179\n", "Epoch 43/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0312 - mae: 0.0312 - val_loss: 0.0126 - val_mae: 0.0126\n", "Epoch 44/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0292 - mae: 0.0292 - val_loss: 0.0197 - val_mae: 0.0197\n", "Epoch 45/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0311 - mae: 0.0311 - val_loss: 0.0189 - val_mae: 0.0189\n", "Epoch 46/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0315 - mae: 0.0315 - val_loss: 0.0131 - val_mae: 0.0131\n", "Epoch 47/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0301 - mae: 0.0301 - val_loss: 0.0170 - val_mae: 0.0170\n", "Epoch 48/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0320 - mae: 0.0320 - val_loss: 0.0161 - val_mae: 0.0161\n", "Epoch 49/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0312 - mae: 0.0312 - val_loss: 0.0166 - val_mae: 0.0166\n", "Epoch 50/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0302 - mae: 0.0302 - val_loss: 0.0149 - val_mae: 0.0149\n", "Epoch 51/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0289 - mae: 0.0289 - val_loss: 0.0127 - val_mae: 0.0127\n", "Epoch 52/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0324 - mae: 0.0324 - val_loss: 0.0129 - val_mae: 0.0129\n", "Epoch 53/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0304 - mae: 0.0304 - val_loss: 0.0131 - val_mae: 0.0131\n", "Epoch 54/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0306 - mae: 0.0306 - val_loss: 0.0155 - val_mae: 0.0155\n", "Epoch 55/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0289 - mae: 0.0289 - val_loss: 0.0141 - val_mae: 0.0141\n", "Epoch 56/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0300 - mae: 0.0300 - val_loss: 0.0125 - val_mae: 0.0125\n", "Epoch 57/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0269 - mae: 0.0269 - val_loss: 0.0123 - val_mae: 0.0123\n", "Epoch 58/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0284 - mae: 0.0284 - val_loss: 0.0149 - val_mae: 0.0149\n", "Epoch 59/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0284 - mae: 0.0284 - val_loss: 0.0118 - val_mae: 0.0118\n", "Epoch 60/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0276 - mae: 0.0276 - val_loss: 0.0129 - val_mae: 0.0129\n", "Epoch 61/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0306 - mae: 0.0306 - val_loss: 0.0135 - val_mae: 0.0135\n", "Epoch 62/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0276 - mae: 0.0276 - val_loss: 0.0131 - val_mae: 0.0131\n", "Epoch 63/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0292 - mae: 0.0292 - val_loss: 0.0176 - val_mae: 0.0176\n", "Epoch 64/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0267 - mae: 0.0267 - val_loss: 0.0172 - val_mae: 0.0172\n", "Epoch 65/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0273 - mae: 0.0273 - val_loss: 0.0157 - val_mae: 0.0157\n", "Epoch 66/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0297 - mae: 0.0297 - val_loss: 0.0137 - val_mae: 0.0137\n", "Epoch 67/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0273 - mae: 0.0273 - val_loss: 0.0162 - val_mae: 0.0162\n", "Epoch 68/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0290 - mae: 0.0290 - val_loss: 0.0117 - val_mae: 0.0117\n", "Epoch 69/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0271 - mae: 0.0271 - val_loss: 0.0190 - val_mae: 0.0190\n", "Epoch 70/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0270 - mae: 0.0270 - val_loss: 0.0134 - val_mae: 0.0134\n", "Epoch 71/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0272 - mae: 0.0272 - val_loss: 0.0119 - val_mae: 0.0119\n", "Epoch 72/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0295 - mae: 0.0295 - val_loss: 0.0148 - val_mae: 0.0148\n", "Epoch 73/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0282 - mae: 0.0282 - val_loss: 0.0151 - val_mae: 0.0151\n", "Epoch 74/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0288 - mae: 0.0288 - val_loss: 0.0193 - val_mae: 0.0193\n", "Epoch 75/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0293 - mae: 0.0293 - val_loss: 0.0134 - val_mae: 0.0134\n", "Epoch 76/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0269 - mae: 0.0269 - val_loss: 0.0143 - val_mae: 0.0143\n", "Epoch 77/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0282 - mae: 0.0282 - val_loss: 0.0151 - val_mae: 0.0151\n", "Epoch 78/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0267 - mae: 0.0267 - val_loss: 0.0123 - val_mae: 0.0123\n", "Epoch 79/100\n", "17/17 [==============================] - 0s 18ms/step - loss: 0.0285 - mae: 0.0285 - val_loss: 0.0128 - val_mae: 0.0128\n", "Epoch 80/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0278 - mae: 0.0278 - val_loss: 0.0128 - val_mae: 0.0128\n", "Epoch 81/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0287 - mae: 0.0287 - val_loss: 0.0118 - val_mae: 0.0118\n", "Epoch 82/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0275 - mae: 0.0275 - val_loss: 0.0210 - val_mae: 0.0210\n", "Epoch 83/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0282 - mae: 0.0282 - val_loss: 0.0140 - val_mae: 0.0140\n", "Epoch 84/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0288 - mae: 0.0288 - val_loss: 0.0132 - val_mae: 0.0132\n", "Epoch 85/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0284 - mae: 0.0284 - val_loss: 0.0113 - val_mae: 0.0113\n", "Epoch 86/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0283 - mae: 0.0283 - val_loss: 0.0165 - val_mae: 0.0165\n", "Epoch 87/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0274 - mae: 0.0274 - val_loss: 0.0126 - val_mae: 0.0126\n", "Epoch 88/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0263 - mae: 0.0263 - val_loss: 0.0129 - val_mae: 0.0129\n", "Epoch 89/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0278 - mae: 0.0278 - val_loss: 0.0122 - val_mae: 0.0122\n", "Epoch 90/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0274 - mae: 0.0274 - val_loss: 0.0142 - val_mae: 0.0142\n", "Epoch 91/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0268 - mae: 0.0268 - val_loss: 0.0142 - val_mae: 0.0142\n", "Epoch 92/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0299 - mae: 0.0299 - val_loss: 0.0188 - val_mae: 0.0188\n", "Epoch 93/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0268 - mae: 0.0268 - val_loss: 0.0116 - val_mae: 0.0116\n", "Epoch 94/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0274 - mae: 0.0274 - val_loss: 0.0116 - val_mae: 0.0116\n", "Epoch 95/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0276 - mae: 0.0276 - val_loss: 0.0114 - val_mae: 0.0114\n", "Epoch 96/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0271 - mae: 0.0271 - val_loss: 0.0139 - val_mae: 0.0139\n", "Epoch 97/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0262 - mae: 0.0262 - val_loss: 0.0150 - val_mae: 0.0150\n", "Epoch 98/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0273 - mae: 0.0273 - val_loss: 0.0119 - val_mae: 0.0119\n", "Epoch 99/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0271 - mae: 0.0271 - val_loss: 0.0108 - val_mae: 0.0108\n", "Epoch 100/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0264 - mae: 0.0264 - val_loss: 0.0146 - val_mae: 0.0146\n", "MSE: 1.6E-03, RMSE: 0.04, MAE: 0.019, MAPE: 6.3 %, R_2: 0.15\n", "Epoch 1/100\n", "17/17 [==============================] - 3s 44ms/step - loss: 0.0265 - mae: 0.0265 - val_loss: 0.0123 - val_mae: 0.0123\n", "Epoch 2/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0260 - mae: 0.0260 - val_loss: 0.0108 - val_mae: 0.0108\n", "Epoch 3/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0277 - mae: 0.0277 - val_loss: 0.0183 - val_mae: 0.0183\n", "Epoch 4/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0267 - mae: 0.0267 - val_loss: 0.0151 - val_mae: 0.0151\n", "Epoch 5/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0270 - mae: 0.0270 - val_loss: 0.0197 - val_mae: 0.0197\n", "Epoch 6/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0292 - mae: 0.0292 - val_loss: 0.0111 - val_mae: 0.0111\n", "Epoch 7/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0258 - mae: 0.0258 - val_loss: 0.0143 - val_mae: 0.0143\n", "Epoch 8/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0272 - mae: 0.0272 - val_loss: 0.0170 - val_mae: 0.0170\n", "Epoch 9/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0276 - mae: 0.0276 - val_loss: 0.0111 - val_mae: 0.0111\n", "Epoch 10/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0283 - mae: 0.0283 - val_loss: 0.0119 - val_mae: 0.0119\n", "Epoch 11/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0292 - mae: 0.0292 - val_loss: 0.0119 - val_mae: 0.0119\n", "Epoch 12/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0268 - mae: 0.0268 - val_loss: 0.0146 - val_mae: 0.0146\n", "Epoch 13/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0281 - mae: 0.0281 - val_loss: 0.0135 - val_mae: 0.0135\n", "Epoch 14/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0267 - mae: 0.0267 - val_loss: 0.0128 - val_mae: 0.0128\n", "Epoch 15/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0269 - mae: 0.0269 - val_loss: 0.0142 - val_mae: 0.0142\n", "Epoch 16/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0260 - mae: 0.0260 - val_loss: 0.0124 - val_mae: 0.0124\n", "Epoch 17/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0284 - mae: 0.0284 - val_loss: 0.0138 - val_mae: 0.0138\n", "Epoch 18/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0257 - mae: 0.0257 - val_loss: 0.0139 - val_mae: 0.0139\n", "Epoch 19/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0268 - mae: 0.0268 - val_loss: 0.0138 - val_mae: 0.0138\n", "Epoch 20/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0263 - mae: 0.0263 - val_loss: 0.0123 - val_mae: 0.0123\n", "Epoch 21/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0258 - mae: 0.0258 - val_loss: 0.0139 - val_mae: 0.0139\n", "Epoch 22/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0257 - mae: 0.0257 - val_loss: 0.0113 - val_mae: 0.0113\n", "Epoch 23/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0266 - mae: 0.0266 - val_loss: 0.0143 - val_mae: 0.0143\n", "Epoch 24/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0262 - mae: 0.0262 - val_loss: 0.0122 - val_mae: 0.0122\n", "Epoch 25/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0264 - mae: 0.0264 - val_loss: 0.0107 - val_mae: 0.0107\n", "Epoch 26/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0256 - mae: 0.0256 - val_loss: 0.0122 - val_mae: 0.0122\n", "Epoch 27/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0258 - mae: 0.0258 - val_loss: 0.0192 - val_mae: 0.0192\n", "Epoch 28/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0264 - mae: 0.0264 - val_loss: 0.0117 - val_mae: 0.0117\n", "Epoch 29/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0277 - mae: 0.0277 - val_loss: 0.0130 - val_mae: 0.0130\n", "Epoch 30/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0262 - mae: 0.0262 - val_loss: 0.0121 - val_mae: 0.0121\n", "Epoch 31/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0261 - mae: 0.0261 - val_loss: 0.0156 - val_mae: 0.0156\n", "Epoch 32/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0259 - mae: 0.0259 - val_loss: 0.0114 - val_mae: 0.0114\n", "Epoch 33/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0257 - mae: 0.0257 - val_loss: 0.0110 - val_mae: 0.0110\n", "Epoch 34/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0267 - mae: 0.0267 - val_loss: 0.0157 - val_mae: 0.0157\n", "Epoch 35/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0250 - mae: 0.0250 - val_loss: 0.0129 - val_mae: 0.0129\n", "Epoch 36/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0251 - mae: 0.0251 - val_loss: 0.0119 - val_mae: 0.0119\n", "Epoch 37/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0254 - mae: 0.0254 - val_loss: 0.0113 - val_mae: 0.0113\n", "Epoch 38/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0248 - mae: 0.0248 - val_loss: 0.0116 - val_mae: 0.0116\n", "Epoch 39/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0253 - mae: 0.0253 - val_loss: 0.0169 - val_mae: 0.0169\n", "Epoch 40/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0264 - mae: 0.0264 - val_loss: 0.0131 - val_mae: 0.0131\n", "Epoch 41/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0267 - mae: 0.0267 - val_loss: 0.0138 - val_mae: 0.0138\n", "Epoch 42/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0253 - mae: 0.0253 - val_loss: 0.0111 - val_mae: 0.0111\n", "Epoch 43/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0266 - mae: 0.0266 - val_loss: 0.0143 - val_mae: 0.0143\n", "Epoch 44/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0249 - mae: 0.0249 - val_loss: 0.0114 - val_mae: 0.0114\n", "Epoch 45/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0259 - mae: 0.0259 - val_loss: 0.0163 - val_mae: 0.0163\n", "Epoch 46/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0261 - mae: 0.0261 - val_loss: 0.0136 - val_mae: 0.0136\n", "Epoch 47/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0259 - mae: 0.0259 - val_loss: 0.0115 - val_mae: 0.0115\n", "Epoch 48/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0258 - mae: 0.0258 - val_loss: 0.0127 - val_mae: 0.0127\n", "Epoch 49/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0253 - mae: 0.0253 - val_loss: 0.0139 - val_mae: 0.0139\n", "Epoch 50/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0261 - mae: 0.0261 - val_loss: 0.0129 - val_mae: 0.0129\n", "Epoch 51/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0251 - mae: 0.0251 - val_loss: 0.0119 - val_mae: 0.0119\n", "Epoch 52/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0255 - mae: 0.0255 - val_loss: 0.0116 - val_mae: 0.0116\n", "Epoch 53/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0265 - mae: 0.0265 - val_loss: 0.0126 - val_mae: 0.0126\n", "Epoch 54/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0259 - mae: 0.0259 - val_loss: 0.0203 - val_mae: 0.0203\n", "Epoch 55/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0264 - mae: 0.0264 - val_loss: 0.0113 - val_mae: 0.0113\n", "Epoch 56/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0258 - mae: 0.0258 - val_loss: 0.0130 - val_mae: 0.0130\n", "Epoch 57/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0257 - mae: 0.0257 - val_loss: 0.0166 - val_mae: 0.0166\n", "Epoch 58/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0235 - mae: 0.0235 - val_loss: 0.0115 - val_mae: 0.0115\n", "Epoch 59/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0263 - mae: 0.0263 - val_loss: 0.0122 - val_mae: 0.0122\n", "Epoch 60/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0252 - mae: 0.0252 - val_loss: 0.0114 - val_mae: 0.0114\n", "Epoch 61/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0254 - mae: 0.0254 - val_loss: 0.0149 - val_mae: 0.0149\n", "Epoch 62/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0259 - mae: 0.0259 - val_loss: 0.0118 - val_mae: 0.0118\n", "Epoch 63/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0259 - mae: 0.0259 - val_loss: 0.0102 - val_mae: 0.0102\n", "Epoch 64/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0247 - mae: 0.0247 - val_loss: 0.0107 - val_mae: 0.0107\n", "Epoch 65/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0261 - mae: 0.0261 - val_loss: 0.0117 - val_mae: 0.0117\n", "Epoch 66/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0241 - mae: 0.0241 - val_loss: 0.0142 - val_mae: 0.0142\n", "Epoch 67/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0256 - mae: 0.0256 - val_loss: 0.0128 - val_mae: 0.0128\n", "Epoch 68/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0252 - mae: 0.0252 - val_loss: 0.0123 - val_mae: 0.0123\n", "Epoch 69/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0241 - mae: 0.0241 - val_loss: 0.0139 - val_mae: 0.0139\n", "Epoch 70/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0246 - mae: 0.0246 - val_loss: 0.0129 - val_mae: 0.0129\n", "Epoch 71/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0250 - mae: 0.0250 - val_loss: 0.0140 - val_mae: 0.0140\n", "Epoch 72/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0246 - mae: 0.0246 - val_loss: 0.0122 - val_mae: 0.0122\n", "Epoch 73/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0254 - mae: 0.0254 - val_loss: 0.0135 - val_mae: 0.0135\n", "Epoch 74/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0239 - mae: 0.0239 - val_loss: 0.0126 - val_mae: 0.0126\n", "Epoch 75/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0256 - mae: 0.0256 - val_loss: 0.0123 - val_mae: 0.0123\n", "Epoch 76/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0244 - mae: 0.0244 - val_loss: 0.0105 - val_mae: 0.0105\n", "Epoch 77/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0239 - mae: 0.0239 - val_loss: 0.0112 - val_mae: 0.0112\n", "Epoch 78/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0255 - mae: 0.0255 - val_loss: 0.0175 - val_mae: 0.0175\n", "Epoch 79/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0235 - mae: 0.0235 - val_loss: 0.0112 - val_mae: 0.0112\n", "Epoch 80/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0249 - mae: 0.0249 - val_loss: 0.0101 - val_mae: 0.0101\n", "Epoch 81/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0249 - mae: 0.0249 - val_loss: 0.0133 - val_mae: 0.0133\n", "Epoch 82/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0246 - mae: 0.0246 - val_loss: 0.0121 - val_mae: 0.0121\n", "Epoch 83/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0243 - mae: 0.0243 - val_loss: 0.0121 - val_mae: 0.0121\n", "Epoch 84/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0253 - mae: 0.0253 - val_loss: 0.0166 - val_mae: 0.0166\n", "Epoch 85/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0253 - mae: 0.0253 - val_loss: 0.0122 - val_mae: 0.0122\n", "Epoch 86/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0231 - mae: 0.0231 - val_loss: 0.0160 - val_mae: 0.0160\n", "Epoch 87/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0245 - mae: 0.0245 - val_loss: 0.0129 - val_mae: 0.0129\n", "Epoch 88/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0259 - mae: 0.0259 - val_loss: 0.0132 - val_mae: 0.0132\n", "Epoch 89/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0247 - mae: 0.0247 - val_loss: 0.0127 - val_mae: 0.0127\n", "Epoch 90/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0241 - mae: 0.0241 - val_loss: 0.0140 - val_mae: 0.0140\n", "Epoch 91/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0239 - mae: 0.0239 - val_loss: 0.0117 - val_mae: 0.0117\n", "Epoch 92/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0245 - mae: 0.0245 - val_loss: 0.0113 - val_mae: 0.0113\n", "Epoch 93/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0252 - mae: 0.0252 - val_loss: 0.0113 - val_mae: 0.0113\n", "Epoch 94/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0235 - mae: 0.0235 - val_loss: 0.0110 - val_mae: 0.0110\n", "Epoch 95/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0242 - mae: 0.0242 - val_loss: 0.0144 - val_mae: 0.0144\n", "Epoch 96/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0261 - mae: 0.0261 - val_loss: 0.0103 - val_mae: 0.0103\n", "Epoch 97/100\n", "17/17 [==============================] - 0s 8ms/step - loss: 0.0249 - mae: 0.0249 - val_loss: 0.0150 - val_mae: 0.0150\n", "Epoch 98/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0244 - mae: 0.0244 - val_loss: 0.0130 - val_mae: 0.0130\n", "Epoch 99/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0249 - mae: 0.0249 - val_loss: 0.0099 - val_mae: 0.0099\n", "Epoch 100/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0257 - mae: 0.0257 - val_loss: 0.0112 - val_mae: 0.0112\n", "MSE: 3.9E-04, RMSE: 0.02, MAE: 0.014, MAPE: 5.2 %, R_2: 0.295\n", "Epoch 1/100\n", "17/17 [==============================] - 3s 49ms/step - loss: 0.0223 - mae: 0.0223 - val_loss: 0.0144 - val_mae: 0.0144\n", "Epoch 2/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0249 - mae: 0.0249 - val_loss: 0.0076 - val_mae: 0.0076\n", "Epoch 3/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0239 - mae: 0.0239 - val_loss: 0.0092 - val_mae: 0.0092\n", "Epoch 4/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0237 - mae: 0.0237 - val_loss: 0.0091 - val_mae: 0.0091\n", "Epoch 5/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0234 - mae: 0.0234 - val_loss: 0.0134 - val_mae: 0.0134\n", "Epoch 6/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0249 - mae: 0.0249 - val_loss: 0.0141 - val_mae: 0.0141\n", "Epoch 7/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0237 - mae: 0.0237 - val_loss: 0.0092 - val_mae: 0.0092\n", "Epoch 8/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0238 - mae: 0.0238 - val_loss: 0.0093 - val_mae: 0.0093\n", "Epoch 9/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0234 - mae: 0.0234 - val_loss: 0.0086 - val_mae: 0.0086\n", "Epoch 10/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0246 - mae: 0.0246 - val_loss: 0.0145 - val_mae: 0.0145\n", "Epoch 11/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0245 - mae: 0.0245 - val_loss: 0.0119 - val_mae: 0.0119\n", "Epoch 12/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0230 - mae: 0.0230 - val_loss: 0.0079 - val_mae: 0.0079\n", "Epoch 13/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0249 - mae: 0.0249 - val_loss: 0.0087 - val_mae: 0.0087\n", "Epoch 14/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0237 - mae: 0.0237 - val_loss: 0.0096 - val_mae: 0.0096\n", "Epoch 15/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0246 - mae: 0.0246 - val_loss: 0.0137 - val_mae: 0.0137\n", "Epoch 16/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0234 - mae: 0.0234 - val_loss: 0.0135 - val_mae: 0.0135\n", "Epoch 17/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0238 - mae: 0.0238 - val_loss: 0.0086 - val_mae: 0.0086\n", "Epoch 18/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0235 - mae: 0.0235 - val_loss: 0.0084 - val_mae: 0.0084\n", "Epoch 19/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0246 - mae: 0.0246 - val_loss: 0.0092 - val_mae: 0.0092\n", "Epoch 20/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0231 - mae: 0.0231 - val_loss: 0.0137 - val_mae: 0.0137\n", "Epoch 21/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0242 - mae: 0.0242 - val_loss: 0.0122 - val_mae: 0.0122\n", "Epoch 22/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0238 - mae: 0.0238 - val_loss: 0.0123 - val_mae: 0.0123\n", "Epoch 23/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0240 - mae: 0.0240 - val_loss: 0.0146 - val_mae: 0.0146\n", "Epoch 24/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0238 - mae: 0.0238 - val_loss: 0.0113 - val_mae: 0.0113\n", "Epoch 25/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0235 - mae: 0.0235 - val_loss: 0.0078 - val_mae: 0.0078\n", "Epoch 26/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0248 - mae: 0.0248 - val_loss: 0.0092 - val_mae: 0.0092\n", "Epoch 27/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0237 - mae: 0.0237 - val_loss: 0.0129 - val_mae: 0.0129\n", "Epoch 28/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0244 - mae: 0.0244 - val_loss: 0.0122 - val_mae: 0.0122\n", "Epoch 29/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0238 - mae: 0.0238 - val_loss: 0.0080 - val_mae: 0.0080\n", "Epoch 30/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0241 - mae: 0.0241 - val_loss: 0.0097 - val_mae: 0.0097\n", "Epoch 31/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0236 - mae: 0.0236 - val_loss: 0.0082 - val_mae: 0.0082\n", "Epoch 32/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0228 - mae: 0.0228 - val_loss: 0.0166 - val_mae: 0.0166\n", "Epoch 33/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0241 - mae: 0.0241 - val_loss: 0.0078 - val_mae: 0.0078\n", "Epoch 34/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0245 - mae: 0.0245 - val_loss: 0.0101 - val_mae: 0.0101\n", "Epoch 35/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0236 - mae: 0.0236 - val_loss: 0.0081 - val_mae: 0.0081\n", "Epoch 36/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0236 - mae: 0.0236 - val_loss: 0.0171 - val_mae: 0.0171\n", "Epoch 37/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0249 - mae: 0.0249 - val_loss: 0.0148 - val_mae: 0.0148\n", "Epoch 38/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0239 - mae: 0.0239 - val_loss: 0.0103 - val_mae: 0.0103\n", "Epoch 39/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0235 - mae: 0.0235 - val_loss: 0.0080 - val_mae: 0.0080\n", "Epoch 40/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0222 - mae: 0.0222 - val_loss: 0.0089 - val_mae: 0.0089\n", "Epoch 41/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0230 - mae: 0.0230 - val_loss: 0.0081 - val_mae: 0.0081\n", "Epoch 42/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0244 - mae: 0.0244 - val_loss: 0.0081 - val_mae: 0.0081\n", "Epoch 43/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0242 - mae: 0.0242 - val_loss: 0.0077 - val_mae: 0.0077\n", "Epoch 44/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0239 - mae: 0.0239 - val_loss: 0.0127 - val_mae: 0.0127\n", "Epoch 45/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0230 - mae: 0.0230 - val_loss: 0.0119 - val_mae: 0.0119\n", "Epoch 46/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0228 - mae: 0.0228 - val_loss: 0.0102 - val_mae: 0.0102\n", "Epoch 47/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0231 - mae: 0.0231 - val_loss: 0.0129 - val_mae: 0.0129\n", "Epoch 48/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0230 - mae: 0.0230 - val_loss: 0.0082 - val_mae: 0.0082\n", "Epoch 49/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0241 - mae: 0.0241 - val_loss: 0.0108 - val_mae: 0.0108\n", "Epoch 50/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0245 - mae: 0.0245 - val_loss: 0.0124 - val_mae: 0.0124\n", "Epoch 51/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0259 - mae: 0.0259 - val_loss: 0.0091 - val_mae: 0.0091\n", "Epoch 52/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0240 - mae: 0.0240 - val_loss: 0.0097 - val_mae: 0.0097\n", "Epoch 53/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0220 - mae: 0.0220 - val_loss: 0.0134 - val_mae: 0.0134\n", "Epoch 54/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0239 - mae: 0.0239 - val_loss: 0.0086 - val_mae: 0.0086\n", "Epoch 55/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0243 - mae: 0.0243 - val_loss: 0.0096 - val_mae: 0.0096\n", "Epoch 56/100\n", "17/17 [==============================] - 0s 18ms/step - loss: 0.0237 - mae: 0.0237 - val_loss: 0.0117 - val_mae: 0.0117\n", "Epoch 57/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0227 - mae: 0.0227 - val_loss: 0.0126 - val_mae: 0.0126\n", "Epoch 58/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0226 - mae: 0.0226 - val_loss: 0.0110 - val_mae: 0.0110\n", "Epoch 59/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0226 - mae: 0.0226 - val_loss: 0.0086 - val_mae: 0.0086\n", "Epoch 60/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0227 - mae: 0.0227 - val_loss: 0.0131 - val_mae: 0.0131\n", "Epoch 61/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0228 - mae: 0.0228 - val_loss: 0.0120 - val_mae: 0.0120\n", "Epoch 62/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0243 - mae: 0.0243 - val_loss: 0.0076 - val_mae: 0.0076\n", "Epoch 63/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0233 - mae: 0.0233 - val_loss: 0.0127 - val_mae: 0.0127\n", "Epoch 64/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0231 - mae: 0.0231 - val_loss: 0.0113 - val_mae: 0.0113\n", "Epoch 65/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0243 - mae: 0.0243 - val_loss: 0.0077 - val_mae: 0.0077\n", "Epoch 66/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0222 - mae: 0.0222 - val_loss: 0.0099 - val_mae: 0.0099\n", "Epoch 67/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0232 - mae: 0.0232 - val_loss: 0.0097 - val_mae: 0.0097\n", "Epoch 68/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0221 - mae: 0.0221 - val_loss: 0.0164 - val_mae: 0.0164\n", "Epoch 69/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0234 - mae: 0.0234 - val_loss: 0.0088 - val_mae: 0.0088\n", "Epoch 70/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0232 - mae: 0.0232 - val_loss: 0.0098 - val_mae: 0.0098\n", "Epoch 71/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0232 - mae: 0.0232 - val_loss: 0.0140 - val_mae: 0.0140\n", "Epoch 72/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0250 - mae: 0.0250 - val_loss: 0.0105 - val_mae: 0.0105\n", "Epoch 73/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0224 - mae: 0.0224 - val_loss: 0.0086 - val_mae: 0.0086\n", "Epoch 74/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0236 - mae: 0.0236 - val_loss: 0.0088 - val_mae: 0.0088\n", "Epoch 75/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0216 - mae: 0.0216 - val_loss: 0.0101 - val_mae: 0.0101\n", "Epoch 76/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0220 - mae: 0.0220 - val_loss: 0.0078 - val_mae: 0.0078\n", "Epoch 77/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0225 - mae: 0.0225 - val_loss: 0.0084 - val_mae: 0.0084\n", "Epoch 78/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0230 - mae: 0.0230 - val_loss: 0.0120 - val_mae: 0.0120\n", "Epoch 79/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0218 - mae: 0.0218 - val_loss: 0.0104 - val_mae: 0.0104\n", "Epoch 80/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0227 - mae: 0.0227 - val_loss: 0.0137 - val_mae: 0.0137\n", "Epoch 81/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0239 - mae: 0.0239 - val_loss: 0.0107 - val_mae: 0.0107\n", "Epoch 82/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0233 - mae: 0.0233 - val_loss: 0.0117 - val_mae: 0.0117\n", "Epoch 83/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0227 - mae: 0.0227 - val_loss: 0.0109 - val_mae: 0.0109\n", "Epoch 84/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0233 - mae: 0.0233 - val_loss: 0.0098 - val_mae: 0.0098\n", "Epoch 85/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0232 - mae: 0.0232 - val_loss: 0.0155 - val_mae: 0.0155\n", "Epoch 86/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0219 - mae: 0.0219 - val_loss: 0.0101 - val_mae: 0.0101\n", "Epoch 87/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0225 - mae: 0.0225 - val_loss: 0.0109 - val_mae: 0.0109\n", "Epoch 88/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0230 - mae: 0.0230 - val_loss: 0.0080 - val_mae: 0.0080\n", "Epoch 89/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0224 - mae: 0.0224 - val_loss: 0.0101 - val_mae: 0.0101\n", "Epoch 90/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0233 - mae: 0.0233 - val_loss: 0.0183 - val_mae: 0.0183\n", "Epoch 91/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0243 - mae: 0.0243 - val_loss: 0.0097 - val_mae: 0.0097\n", "Epoch 92/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0228 - mae: 0.0228 - val_loss: 0.0088 - val_mae: 0.0088\n", "Epoch 93/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0233 - mae: 0.0233 - val_loss: 0.0097 - val_mae: 0.0097\n", "Epoch 94/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0213 - mae: 0.0213 - val_loss: 0.0148 - val_mae: 0.0148\n", "Epoch 95/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0235 - mae: 0.0235 - val_loss: 0.0077 - val_mae: 0.0077\n", "Epoch 96/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0237 - mae: 0.0237 - val_loss: 0.0139 - val_mae: 0.0139\n", "Epoch 97/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0221 - mae: 0.0221 - val_loss: 0.0091 - val_mae: 0.0091\n", "Epoch 98/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0228 - mae: 0.0228 - val_loss: 0.0115 - val_mae: 0.0115\n", "Epoch 99/100\n", "17/17 [==============================] - 0s 8ms/step - loss: 0.0229 - mae: 0.0229 - val_loss: 0.0138 - val_mae: 0.0138\n", "Epoch 100/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0228 - mae: 0.0228 - val_loss: 0.0136 - val_mae: 0.0136\n", "MSE: 4.2E-04, RMSE: 0.02, MAE: 0.017, MAPE: 6.48 %, R_2: -0.01\n", "Epoch 1/100\n", "17/17 [==============================] - 3s 48ms/step - loss: 0.0237 - mae: 0.0237 - val_loss: 0.0122 - val_mae: 0.0122\n", "Epoch 2/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0223 - mae: 0.0223 - val_loss: 0.0109 - val_mae: 0.0109\n", "Epoch 3/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0239 - mae: 0.0239 - val_loss: 0.0176 - val_mae: 0.0176\n", "Epoch 4/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0237 - mae: 0.0237 - val_loss: 0.0104 - val_mae: 0.0104\n", "Epoch 5/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0233 - mae: 0.0233 - val_loss: 0.0131 - val_mae: 0.0131\n", "Epoch 6/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0235 - mae: 0.0235 - val_loss: 0.0184 - val_mae: 0.0184\n", "Epoch 7/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0226 - mae: 0.0226 - val_loss: 0.0109 - val_mae: 0.0109\n", "Epoch 8/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0239 - mae: 0.0239 - val_loss: 0.0147 - val_mae: 0.0147\n", "Epoch 9/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0237 - mae: 0.0237 - val_loss: 0.0107 - val_mae: 0.0107\n", "Epoch 10/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0225 - mae: 0.0225 - val_loss: 0.0151 - val_mae: 0.0151\n", "Epoch 11/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0236 - mae: 0.0236 - val_loss: 0.0133 - val_mae: 0.0133\n", "Epoch 12/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0222 - mae: 0.0222 - val_loss: 0.0118 - val_mae: 0.0118\n", "Epoch 13/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0228 - mae: 0.0228 - val_loss: 0.0116 - val_mae: 0.0116\n", "Epoch 14/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0230 - mae: 0.0230 - val_loss: 0.0116 - val_mae: 0.0116\n", "Epoch 15/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0234 - mae: 0.0234 - val_loss: 0.0136 - val_mae: 0.0136\n", "Epoch 16/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0229 - mae: 0.0229 - val_loss: 0.0110 - val_mae: 0.0110\n", "Epoch 17/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0225 - mae: 0.0225 - val_loss: 0.0113 - val_mae: 0.0113\n", "Epoch 18/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0240 - mae: 0.0240 - val_loss: 0.0194 - val_mae: 0.0194\n", "Epoch 19/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0238 - mae: 0.0238 - val_loss: 0.0149 - val_mae: 0.0149\n", "Epoch 20/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0229 - mae: 0.0229 - val_loss: 0.0124 - val_mae: 0.0124\n", "Epoch 21/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0231 - mae: 0.0231 - val_loss: 0.0135 - val_mae: 0.0135\n", "Epoch 22/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0218 - mae: 0.0218 - val_loss: 0.0133 - val_mae: 0.0133\n", "Epoch 23/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0230 - mae: 0.0230 - val_loss: 0.0147 - val_mae: 0.0147\n", "Epoch 24/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0217 - mae: 0.0217 - val_loss: 0.0149 - val_mae: 0.0149\n", "Epoch 25/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0226 - mae: 0.0226 - val_loss: 0.0110 - val_mae: 0.0110\n", "Epoch 26/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0242 - mae: 0.0242 - val_loss: 0.0120 - val_mae: 0.0120\n", "Epoch 27/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0229 - mae: 0.0229 - val_loss: 0.0173 - val_mae: 0.0173\n", "Epoch 28/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0227 - mae: 0.0227 - val_loss: 0.0112 - val_mae: 0.0112\n", "Epoch 29/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0221 - mae: 0.0221 - val_loss: 0.0131 - val_mae: 0.0131\n", "Epoch 30/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0230 - mae: 0.0230 - val_loss: 0.0107 - val_mae: 0.0107\n", "Epoch 31/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0225 - mae: 0.0225 - val_loss: 0.0123 - val_mae: 0.0123\n", "Epoch 32/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0227 - mae: 0.0227 - val_loss: 0.0136 - val_mae: 0.0136\n", "Epoch 33/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0227 - mae: 0.0227 - val_loss: 0.0160 - val_mae: 0.0160\n", "Epoch 34/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0234 - mae: 0.0234 - val_loss: 0.0107 - val_mae: 0.0107\n", "Epoch 35/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0226 - mae: 0.0226 - val_loss: 0.0112 - val_mae: 0.0112\n", "Epoch 36/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0227 - mae: 0.0227 - val_loss: 0.0132 - val_mae: 0.0132\n", "Epoch 37/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0233 - mae: 0.0233 - val_loss: 0.0119 - val_mae: 0.0119\n", "Epoch 38/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0227 - mae: 0.0227 - val_loss: 0.0120 - val_mae: 0.0120\n", "Epoch 39/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0227 - mae: 0.0227 - val_loss: 0.0132 - val_mae: 0.0132\n", "Epoch 40/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0215 - mae: 0.0215 - val_loss: 0.0144 - val_mae: 0.0144\n", "Epoch 41/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0221 - mae: 0.0221 - val_loss: 0.0165 - val_mae: 0.0165\n", "Epoch 42/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0225 - mae: 0.0225 - val_loss: 0.0101 - val_mae: 0.0101\n", "Epoch 43/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0214 - mae: 0.0214 - val_loss: 0.0156 - val_mae: 0.0156\n", "Epoch 44/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0217 - mae: 0.0217 - val_loss: 0.0105 - val_mae: 0.0105\n", "Epoch 45/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0222 - mae: 0.0222 - val_loss: 0.0139 - val_mae: 0.0139\n", "Epoch 46/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0222 - mae: 0.0222 - val_loss: 0.0129 - val_mae: 0.0129\n", "Epoch 47/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0218 - mae: 0.0218 - val_loss: 0.0128 - val_mae: 0.0128\n", "Epoch 48/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0214 - mae: 0.0214 - val_loss: 0.0133 - val_mae: 0.0133\n", "Epoch 49/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0221 - mae: 0.0221 - val_loss: 0.0129 - val_mae: 0.0129\n", "Epoch 50/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0224 - mae: 0.0224 - val_loss: 0.0104 - val_mae: 0.0104\n", "Epoch 51/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0227 - mae: 0.0227 - val_loss: 0.0183 - val_mae: 0.0183\n", "Epoch 52/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0224 - mae: 0.0224 - val_loss: 0.0123 - val_mae: 0.0123\n", "Epoch 53/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0224 - mae: 0.0224 - val_loss: 0.0153 - val_mae: 0.0153\n", "Epoch 54/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0232 - mae: 0.0232 - val_loss: 0.0132 - val_mae: 0.0132\n", "Epoch 55/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0229 - mae: 0.0229 - val_loss: 0.0116 - val_mae: 0.0116\n", "Epoch 56/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0235 - mae: 0.0235 - val_loss: 0.0121 - val_mae: 0.0121\n", "Epoch 57/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0214 - mae: 0.0214 - val_loss: 0.0149 - val_mae: 0.0149\n", "Epoch 58/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0219 - mae: 0.0219 - val_loss: 0.0135 - val_mae: 0.0135\n", "Epoch 59/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0220 - mae: 0.0220 - val_loss: 0.0123 - val_mae: 0.0123\n", "Epoch 60/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0222 - mae: 0.0222 - val_loss: 0.0151 - val_mae: 0.0151\n", "Epoch 61/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0229 - mae: 0.0229 - val_loss: 0.0112 - val_mae: 0.0112\n", "Epoch 62/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0234 - mae: 0.0234 - val_loss: 0.0111 - val_mae: 0.0111\n", "Epoch 63/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0222 - mae: 0.0222 - val_loss: 0.0133 - val_mae: 0.0133\n", "Epoch 64/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0221 - mae: 0.0221 - val_loss: 0.0125 - val_mae: 0.0125\n", "Epoch 65/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0223 - mae: 0.0223 - val_loss: 0.0123 - val_mae: 0.0123\n", "Epoch 66/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0232 - mae: 0.0232 - val_loss: 0.0124 - val_mae: 0.0124\n", "Epoch 67/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0224 - mae: 0.0224 - val_loss: 0.0139 - val_mae: 0.0139\n", "Epoch 68/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0214 - mae: 0.0214 - val_loss: 0.0115 - val_mae: 0.0115\n", "Epoch 69/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0226 - mae: 0.0226 - val_loss: 0.0140 - val_mae: 0.0140\n", "Epoch 70/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0214 - mae: 0.0214 - val_loss: 0.0123 - val_mae: 0.0123\n", "Epoch 71/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0208 - mae: 0.0208 - val_loss: 0.0123 - val_mae: 0.0123\n", "Epoch 72/100\n", "17/17 [==============================] - 0s 18ms/step - loss: 0.0214 - mae: 0.0214 - val_loss: 0.0136 - val_mae: 0.0136\n", "Epoch 73/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0221 - mae: 0.0221 - val_loss: 0.0119 - val_mae: 0.0119\n", "Epoch 74/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0219 - mae: 0.0219 - val_loss: 0.0103 - val_mae: 0.0103\n", "Epoch 75/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0215 - mae: 0.0215 - val_loss: 0.0137 - val_mae: 0.0137\n", "Epoch 76/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0211 - mae: 0.0211 - val_loss: 0.0117 - val_mae: 0.0117\n", "Epoch 77/100\n", "17/17 [==============================] - 0s 18ms/step - loss: 0.0219 - mae: 0.0219 - val_loss: 0.0132 - val_mae: 0.0132\n", "Epoch 78/100\n", "17/17 [==============================] - 0s 18ms/step - loss: 0.0223 - mae: 0.0223 - val_loss: 0.0116 - val_mae: 0.0116\n", "Epoch 79/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0216 - mae: 0.0216 - val_loss: 0.0117 - val_mae: 0.0117\n", "Epoch 80/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0216 - mae: 0.0216 - val_loss: 0.0146 - val_mae: 0.0146\n", "Epoch 81/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0211 - mae: 0.0211 - val_loss: 0.0153 - val_mae: 0.0153\n", "Epoch 82/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0218 - mae: 0.0218 - val_loss: 0.0119 - val_mae: 0.0119\n", "Epoch 83/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0229 - mae: 0.0229 - val_loss: 0.0120 - val_mae: 0.0120\n", "Epoch 84/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0205 - mae: 0.0205 - val_loss: 0.0125 - val_mae: 0.0125\n", "Epoch 85/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0207 - mae: 0.0207 - val_loss: 0.0108 - val_mae: 0.0108\n", "Epoch 86/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0212 - mae: 0.0212 - val_loss: 0.0130 - val_mae: 0.0130\n", "Epoch 87/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0209 - mae: 0.0209 - val_loss: 0.0110 - val_mae: 0.0110\n", "Epoch 88/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0214 - mae: 0.0214 - val_loss: 0.0117 - val_mae: 0.0117\n", "Epoch 89/100\n", "17/17 [==============================] - 0s 8ms/step - loss: 0.0220 - mae: 0.0220 - val_loss: 0.0188 - val_mae: 0.0188\n", "Epoch 90/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0205 - mae: 0.0205 - val_loss: 0.0121 - val_mae: 0.0121\n", "Epoch 91/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0216 - mae: 0.0216 - val_loss: 0.0104 - val_mae: 0.0104\n", "Epoch 92/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0234 - mae: 0.0234 - val_loss: 0.0151 - val_mae: 0.0151\n", "Epoch 93/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0224 - mae: 0.0224 - val_loss: 0.0150 - val_mae: 0.0150\n", "Epoch 94/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0228 - mae: 0.0228 - val_loss: 0.0115 - val_mae: 0.0115\n", "Epoch 95/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0205 - mae: 0.0205 - val_loss: 0.0108 - val_mae: 0.0108\n", "Epoch 96/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0211 - mae: 0.0211 - val_loss: 0.0132 - val_mae: 0.0132\n", "Epoch 97/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0210 - mae: 0.0210 - val_loss: 0.0126 - val_mae: 0.0126\n", "Epoch 98/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0207 - mae: 0.0207 - val_loss: 0.0175 - val_mae: 0.0175\n", "Epoch 99/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0219 - mae: 0.0219 - val_loss: 0.0141 - val_mae: 0.0141\n", "Epoch 100/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0223 - mae: 0.0223 - val_loss: 0.0109 - val_mae: 0.0109\n", "MSE: 3.8E-04, RMSE: 0.02, MAE: 0.014, MAPE: 5.03 %, R_2: 0.248\n", "Epoch 1/100\n", "17/17 [==============================] - 4s 51ms/step - loss: 0.0223 - mae: 0.0223 - val_loss: 0.0112 - val_mae: 0.0112\n", "Epoch 2/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0213 - mae: 0.0213 - val_loss: 0.0096 - val_mae: 0.0096\n", "Epoch 3/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0223 - mae: 0.0223 - val_loss: 0.0087 - val_mae: 0.0087\n", "Epoch 4/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0208 - mae: 0.0208 - val_loss: 0.0100 - val_mae: 0.0100\n", "Epoch 5/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0207 - mae: 0.0207 - val_loss: 0.0101 - val_mae: 0.0101\n", "Epoch 6/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0201 - mae: 0.0201 - val_loss: 0.0087 - val_mae: 0.0087\n", "Epoch 7/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0218 - mae: 0.0218 - val_loss: 0.0082 - val_mae: 0.0082\n", "Epoch 8/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0212 - mae: 0.0212 - val_loss: 0.0092 - val_mae: 0.0092\n", "Epoch 9/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0212 - mae: 0.0212 - val_loss: 0.0102 - val_mae: 0.0102\n", "Epoch 10/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0201 - mae: 0.0201 - val_loss: 0.0080 - val_mae: 0.0080\n", "Epoch 11/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0218 - mae: 0.0218 - val_loss: 0.0087 - val_mae: 0.0087\n", "Epoch 12/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0213 - mae: 0.0213 - val_loss: 0.0085 - val_mae: 0.0085\n", "Epoch 13/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0212 - mae: 0.0212 - val_loss: 0.0135 - val_mae: 0.0135\n", "Epoch 14/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0206 - mae: 0.0206 - val_loss: 0.0091 - val_mae: 0.0091\n", "Epoch 15/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0194 - mae: 0.0194 - val_loss: 0.0085 - val_mae: 0.0085\n", "Epoch 16/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0207 - mae: 0.0207 - val_loss: 0.0088 - val_mae: 0.0088\n", "Epoch 17/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0202 - mae: 0.0202 - val_loss: 0.0108 - val_mae: 0.0108\n", "Epoch 18/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0210 - mae: 0.0210 - val_loss: 0.0082 - val_mae: 0.0082\n", "Epoch 19/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0209 - mae: 0.0209 - val_loss: 0.0098 - val_mae: 0.0098\n", "Epoch 20/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0209 - mae: 0.0209 - val_loss: 0.0084 - val_mae: 0.0084\n", "Epoch 21/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0216 - mae: 0.0216 - val_loss: 0.0116 - val_mae: 0.0116\n", "Epoch 22/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0204 - mae: 0.0204 - val_loss: 0.0105 - val_mae: 0.0105\n", "Epoch 23/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0201 - mae: 0.0201 - val_loss: 0.0096 - val_mae: 0.0096\n", "Epoch 24/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0217 - mae: 0.0217 - val_loss: 0.0123 - val_mae: 0.0123\n", "Epoch 25/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0211 - mae: 0.0211 - val_loss: 0.0099 - val_mae: 0.0099\n", "Epoch 26/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0209 - mae: 0.0209 - val_loss: 0.0081 - val_mae: 0.0081\n", "Epoch 27/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0206 - mae: 0.0206 - val_loss: 0.0079 - val_mae: 0.0079\n", "Epoch 28/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0220 - mae: 0.0220 - val_loss: 0.0075 - val_mae: 0.0075\n", "Epoch 29/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0203 - mae: 0.0203 - val_loss: 0.0108 - val_mae: 0.0108\n", "Epoch 30/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0201 - mae: 0.0201 - val_loss: 0.0086 - val_mae: 0.0086\n", "Epoch 31/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0209 - mae: 0.0209 - val_loss: 0.0140 - val_mae: 0.0140\n", "Epoch 32/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0212 - mae: 0.0212 - val_loss: 0.0124 - val_mae: 0.0124\n", "Epoch 33/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0203 - mae: 0.0203 - val_loss: 0.0105 - val_mae: 0.0105\n", "Epoch 34/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0205 - mae: 0.0205 - val_loss: 0.0089 - val_mae: 0.0089\n", "Epoch 35/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0199 - mae: 0.0199 - val_loss: 0.0091 - val_mae: 0.0091\n", "Epoch 36/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0203 - mae: 0.0203 - val_loss: 0.0142 - val_mae: 0.0142\n", "Epoch 37/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0200 - mae: 0.0200 - val_loss: 0.0092 - val_mae: 0.0092\n", "Epoch 38/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0191 - mae: 0.0191 - val_loss: 0.0105 - val_mae: 0.0105\n", "Epoch 39/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0199 - mae: 0.0199 - val_loss: 0.0099 - val_mae: 0.0099\n", "Epoch 40/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0200 - mae: 0.0200 - val_loss: 0.0153 - val_mae: 0.0153\n", "Epoch 41/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0211 - mae: 0.0211 - val_loss: 0.0083 - val_mae: 0.0083\n", "Epoch 42/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0205 - mae: 0.0205 - val_loss: 0.0092 - val_mae: 0.0092\n", "Epoch 43/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0209 - mae: 0.0209 - val_loss: 0.0096 - val_mae: 0.0096\n", "Epoch 44/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0216 - mae: 0.0216 - val_loss: 0.0095 - val_mae: 0.0095\n", "Epoch 45/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0203 - mae: 0.0203 - val_loss: 0.0100 - val_mae: 0.0100\n", "Epoch 46/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0195 - mae: 0.0195 - val_loss: 0.0096 - val_mae: 0.0096\n", "Epoch 47/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0204 - mae: 0.0204 - val_loss: 0.0106 - val_mae: 0.0106\n", "Epoch 48/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0213 - mae: 0.0213 - val_loss: 0.0128 - val_mae: 0.0128\n", "Epoch 49/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0207 - mae: 0.0207 - val_loss: 0.0113 - val_mae: 0.0113\n", "Epoch 50/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0201 - mae: 0.0201 - val_loss: 0.0095 - val_mae: 0.0095\n", "Epoch 51/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0211 - mae: 0.0211 - val_loss: 0.0133 - val_mae: 0.0133\n", "Epoch 52/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0207 - mae: 0.0207 - val_loss: 0.0084 - val_mae: 0.0084\n", "Epoch 53/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0209 - mae: 0.0209 - val_loss: 0.0094 - val_mae: 0.0094\n", "Epoch 54/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0207 - mae: 0.0207 - val_loss: 0.0109 - val_mae: 0.0109\n", "Epoch 55/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0208 - mae: 0.0208 - val_loss: 0.0127 - val_mae: 0.0127\n", "Epoch 56/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0200 - mae: 0.0200 - val_loss: 0.0088 - val_mae: 0.0088\n", "Epoch 57/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0216 - mae: 0.0216 - val_loss: 0.0102 - val_mae: 0.0102\n", "Epoch 58/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0202 - mae: 0.0202 - val_loss: 0.0127 - val_mae: 0.0127\n", "Epoch 59/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0214 - mae: 0.0214 - val_loss: 0.0081 - val_mae: 0.0081\n", "Epoch 60/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0206 - mae: 0.0206 - val_loss: 0.0121 - val_mae: 0.0121\n", "Epoch 61/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0204 - mae: 0.0204 - val_loss: 0.0103 - val_mae: 0.0103\n", "Epoch 62/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0199 - mae: 0.0199 - val_loss: 0.0098 - val_mae: 0.0098\n", "Epoch 63/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0191 - mae: 0.0191 - val_loss: 0.0140 - val_mae: 0.0140\n", "Epoch 64/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0208 - mae: 0.0208 - val_loss: 0.0105 - val_mae: 0.0105\n", "Epoch 65/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0203 - mae: 0.0203 - val_loss: 0.0108 - val_mae: 0.0108\n", "Epoch 66/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0194 - mae: 0.0194 - val_loss: 0.0137 - val_mae: 0.0137\n", "Epoch 67/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0208 - mae: 0.0208 - val_loss: 0.0096 - val_mae: 0.0096\n", "Epoch 68/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0206 - mae: 0.0206 - val_loss: 0.0073 - val_mae: 0.0073\n", "Epoch 69/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0211 - mae: 0.0211 - val_loss: 0.0119 - val_mae: 0.0119\n", "Epoch 70/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0211 - mae: 0.0211 - val_loss: 0.0121 - val_mae: 0.0121\n", "Epoch 71/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0210 - mae: 0.0210 - val_loss: 0.0092 - val_mae: 0.0092\n", "Epoch 72/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0199 - mae: 0.0199 - val_loss: 0.0096 - val_mae: 0.0096\n", "Epoch 73/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0213 - mae: 0.0213 - val_loss: 0.0106 - val_mae: 0.0106\n", "Epoch 74/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0193 - mae: 0.0193 - val_loss: 0.0113 - val_mae: 0.0113\n", "Epoch 75/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0202 - mae: 0.0202 - val_loss: 0.0095 - val_mae: 0.0095\n", "Epoch 76/100\n", "17/17 [==============================] - 0s 8ms/step - loss: 0.0203 - mae: 0.0203 - val_loss: 0.0102 - val_mae: 0.0102\n", "Epoch 77/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0202 - mae: 0.0202 - val_loss: 0.0099 - val_mae: 0.0099\n", "Epoch 78/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0187 - mae: 0.0187 - val_loss: 0.0138 - val_mae: 0.0138\n", "Epoch 79/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0204 - mae: 0.0204 - val_loss: 0.0097 - val_mae: 0.0097\n", "Epoch 80/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0197 - mae: 0.0197 - val_loss: 0.0128 - val_mae: 0.0128\n", "Epoch 81/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0206 - mae: 0.0206 - val_loss: 0.0084 - val_mae: 0.0084\n", "Epoch 82/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0196 - mae: 0.0196 - val_loss: 0.0155 - val_mae: 0.0155\n", "Epoch 83/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0196 - mae: 0.0196 - val_loss: 0.0084 - val_mae: 0.0084\n", "Epoch 84/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0196 - mae: 0.0196 - val_loss: 0.0106 - val_mae: 0.0106\n", "Epoch 85/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0205 - mae: 0.0205 - val_loss: 0.0097 - val_mae: 0.0097\n", "Epoch 86/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0194 - mae: 0.0194 - val_loss: 0.0100 - val_mae: 0.0100\n", "Epoch 87/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0203 - mae: 0.0203 - val_loss: 0.0105 - val_mae: 0.0105\n", "Epoch 88/100\n", "17/17 [==============================] - 0s 8ms/step - loss: 0.0193 - mae: 0.0193 - val_loss: 0.0137 - val_mae: 0.0137\n", "Epoch 89/100\n", "17/17 [==============================] - 0s 6ms/step - loss: 0.0190 - mae: 0.0190 - val_loss: 0.0082 - val_mae: 0.0082\n", "Epoch 90/100\n", "17/17 [==============================] - 0s 7ms/step - loss: 0.0193 - mae: 0.0193 - val_loss: 0.0088 - val_mae: 0.0088\n", "Epoch 91/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0185 - mae: 0.0185 - val_loss: 0.0116 - val_mae: 0.0116\n", "Epoch 92/100\n", "17/17 [==============================] - 0s 8ms/step - loss: 0.0216 - mae: 0.0216 - val_loss: 0.0110 - val_mae: 0.0110\n", "Epoch 93/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0205 - mae: 0.0205 - val_loss: 0.0090 - val_mae: 0.0090\n", "Epoch 94/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0191 - mae: 0.0191 - val_loss: 0.0125 - val_mae: 0.0125\n", "Epoch 95/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0202 - mae: 0.0202 - val_loss: 0.0112 - val_mae: 0.0112\n", "Epoch 96/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0194 - mae: 0.0194 - val_loss: 0.0125 - val_mae: 0.0125\n", "Epoch 97/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0209 - mae: 0.0209 - val_loss: 0.0099 - val_mae: 0.0099\n", "Epoch 98/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0201 - mae: 0.0201 - val_loss: 0.0091 - val_mae: 0.0091\n", "Epoch 99/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0199 - mae: 0.0199 - val_loss: 0.0133 - val_mae: 0.0133\n", "Epoch 100/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0192 - mae: 0.0192 - val_loss: 0.0107 - val_mae: 0.0107\n", "WARNING:tensorflow:5 out of the last 13 calls to .predict_function at 0x7f015449dcb0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for more details.\n", "MSE: 4.0E-04, RMSE: 0.02, MAE: 0.014, MAPE: 4.89 %, R_2: 0.377\n", "Epoch 1/100\n", "17/17 [==============================] - 4s 55ms/step - loss: 0.0196 - mae: 0.0196 - val_loss: 0.0102 - val_mae: 0.0102\n", "Epoch 2/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0196 - mae: 0.0196 - val_loss: 0.0079 - val_mae: 0.0079\n", "Epoch 3/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0208 - mae: 0.0208 - val_loss: 0.0114 - val_mae: 0.0114\n", "Epoch 4/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0201 - mae: 0.0201 - val_loss: 0.0092 - val_mae: 0.0092\n", "Epoch 5/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0193 - mae: 0.0193 - val_loss: 0.0098 - val_mae: 0.0098\n", "Epoch 6/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0201 - mae: 0.0201 - val_loss: 0.0146 - val_mae: 0.0146\n", "Epoch 7/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0190 - mae: 0.0190 - val_loss: 0.0104 - val_mae: 0.0104\n", "Epoch 8/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0186 - mae: 0.0186 - val_loss: 0.0107 - val_mae: 0.0107\n", "Epoch 9/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0201 - mae: 0.0201 - val_loss: 0.0101 - val_mae: 0.0101\n", "Epoch 10/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0195 - mae: 0.0195 - val_loss: 0.0114 - val_mae: 0.0114\n", "Epoch 11/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0202 - mae: 0.0202 - val_loss: 0.0081 - val_mae: 0.0081\n", "Epoch 12/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0194 - mae: 0.0194 - val_loss: 0.0114 - val_mae: 0.0114\n", "Epoch 13/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0191 - mae: 0.0191 - val_loss: 0.0123 - val_mae: 0.0123\n", "Epoch 14/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0195 - mae: 0.0195 - val_loss: 0.0104 - val_mae: 0.0104\n", "Epoch 15/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0200 - mae: 0.0200 - val_loss: 0.0103 - val_mae: 0.0103\n", "Epoch 16/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0205 - mae: 0.0205 - val_loss: 0.0136 - val_mae: 0.0136\n", "Epoch 17/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0193 - mae: 0.0193 - val_loss: 0.0125 - val_mae: 0.0125\n", "Epoch 18/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0195 - mae: 0.0195 - val_loss: 0.0088 - val_mae: 0.0088\n", "Epoch 19/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0194 - mae: 0.0194 - val_loss: 0.0091 - val_mae: 0.0091\n", "Epoch 20/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0199 - mae: 0.0199 - val_loss: 0.0102 - val_mae: 0.0102\n", "Epoch 21/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0194 - mae: 0.0194 - val_loss: 0.0127 - val_mae: 0.0127\n", "Epoch 22/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0191 - mae: 0.0191 - val_loss: 0.0083 - val_mae: 0.0083\n", "Epoch 23/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0197 - mae: 0.0197 - val_loss: 0.0091 - val_mae: 0.0091\n", "Epoch 24/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0200 - mae: 0.0200 - val_loss: 0.0077 - val_mae: 0.0077\n", "Epoch 25/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0201 - mae: 0.0201 - val_loss: 0.0089 - val_mae: 0.0089\n", "Epoch 26/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0194 - mae: 0.0194 - val_loss: 0.0111 - val_mae: 0.0111\n", "Epoch 27/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0192 - mae: 0.0192 - val_loss: 0.0084 - val_mae: 0.0084\n", "Epoch 28/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0206 - mae: 0.0206 - val_loss: 0.0127 - val_mae: 0.0127\n", "Epoch 29/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0191 - mae: 0.0191 - val_loss: 0.0119 - val_mae: 0.0119\n", "Epoch 30/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0191 - mae: 0.0191 - val_loss: 0.0087 - val_mae: 0.0087\n", "Epoch 31/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0189 - mae: 0.0189 - val_loss: 0.0104 - val_mae: 0.0104\n", "Epoch 32/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0187 - mae: 0.0187 - val_loss: 0.0127 - val_mae: 0.0127\n", "Epoch 33/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0204 - mae: 0.0204 - val_loss: 0.0088 - val_mae: 0.0088\n", "Epoch 34/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0184 - mae: 0.0184 - val_loss: 0.0089 - val_mae: 0.0089\n", "Epoch 35/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0191 - mae: 0.0191 - val_loss: 0.0126 - val_mae: 0.0126\n", "Epoch 36/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0186 - mae: 0.0186 - val_loss: 0.0122 - val_mae: 0.0122\n", "Epoch 37/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0215 - mae: 0.0215 - val_loss: 0.0079 - val_mae: 0.0079\n", "Epoch 38/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0193 - mae: 0.0193 - val_loss: 0.0085 - val_mae: 0.0085\n", "Epoch 39/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0200 - mae: 0.0200 - val_loss: 0.0099 - val_mae: 0.0099\n", "Epoch 40/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0186 - mae: 0.0186 - val_loss: 0.0160 - val_mae: 0.0160\n", "Epoch 41/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0195 - mae: 0.0195 - val_loss: 0.0078 - val_mae: 0.0078\n", "Epoch 42/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0187 - mae: 0.0187 - val_loss: 0.0097 - val_mae: 0.0097\n", "Epoch 43/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0183 - mae: 0.0183 - val_loss: 0.0122 - val_mae: 0.0122\n", "Epoch 44/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0194 - mae: 0.0194 - val_loss: 0.0121 - val_mae: 0.0121\n", "Epoch 45/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0183 - mae: 0.0183 - val_loss: 0.0101 - val_mae: 0.0101\n", "Epoch 46/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0187 - mae: 0.0187 - val_loss: 0.0092 - val_mae: 0.0092\n", "Epoch 47/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0199 - mae: 0.0199 - val_loss: 0.0110 - val_mae: 0.0110\n", "Epoch 48/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0196 - mae: 0.0196 - val_loss: 0.0112 - val_mae: 0.0112\n", "Epoch 49/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0196 - mae: 0.0196 - val_loss: 0.0084 - val_mae: 0.0084\n", "Epoch 50/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0185 - mae: 0.0185 - val_loss: 0.0081 - val_mae: 0.0081\n", "Epoch 51/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0210 - mae: 0.0210 - val_loss: 0.0121 - val_mae: 0.0121\n", "Epoch 52/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0194 - mae: 0.0194 - val_loss: 0.0103 - val_mae: 0.0103\n", "Epoch 53/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0197 - mae: 0.0197 - val_loss: 0.0081 - val_mae: 0.0081\n", "Epoch 54/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0200 - mae: 0.0200 - val_loss: 0.0109 - val_mae: 0.0109\n", "Epoch 55/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0196 - mae: 0.0196 - val_loss: 0.0140 - val_mae: 0.0140\n", "Epoch 56/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0205 - mae: 0.0205 - val_loss: 0.0111 - val_mae: 0.0111\n", "Epoch 57/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0187 - mae: 0.0187 - val_loss: 0.0095 - val_mae: 0.0095\n", "Epoch 58/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0185 - mae: 0.0185 - val_loss: 0.0111 - val_mae: 0.0111\n", "Epoch 59/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0178 - mae: 0.0178 - val_loss: 0.0094 - val_mae: 0.0094\n", "Epoch 60/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0196 - mae: 0.0196 - val_loss: 0.0086 - val_mae: 0.0086\n", "Epoch 61/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0187 - mae: 0.0187 - val_loss: 0.0091 - val_mae: 0.0091\n", "Epoch 62/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0182 - mae: 0.0182 - val_loss: 0.0116 - val_mae: 0.0116\n", "Epoch 63/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0193 - mae: 0.0193 - val_loss: 0.0120 - val_mae: 0.0120\n", "Epoch 64/100\n", "17/17 [==============================] - 0s 7ms/step - loss: 0.0193 - mae: 0.0193 - val_loss: 0.0126 - val_mae: 0.0126\n", "Epoch 65/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0190 - mae: 0.0190 - val_loss: 0.0098 - val_mae: 0.0098\n", "Epoch 66/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0192 - mae: 0.0192 - val_loss: 0.0121 - val_mae: 0.0121\n", "Epoch 67/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0184 - mae: 0.0184 - val_loss: 0.0117 - val_mae: 0.0117\n", "Epoch 68/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0190 - mae: 0.0190 - val_loss: 0.0089 - val_mae: 0.0089\n", "Epoch 69/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0200 - mae: 0.0200 - val_loss: 0.0083 - val_mae: 0.0083\n", "Epoch 70/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0197 - mae: 0.0197 - val_loss: 0.0137 - val_mae: 0.0137\n", "Epoch 71/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0190 - mae: 0.0190 - val_loss: 0.0097 - val_mae: 0.0097\n", "Epoch 72/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0191 - mae: 0.0191 - val_loss: 0.0079 - val_mae: 0.0079\n", "Epoch 73/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0204 - mae: 0.0204 - val_loss: 0.0091 - val_mae: 0.0091\n", "Epoch 74/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0193 - mae: 0.0193 - val_loss: 0.0099 - val_mae: 0.0099\n", "Epoch 75/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0186 - mae: 0.0186 - val_loss: 0.0096 - val_mae: 0.0096\n", "Epoch 76/100\n", "17/17 [==============================] - 0s 8ms/step - loss: 0.0188 - mae: 0.0188 - val_loss: 0.0101 - val_mae: 0.0101\n", "Epoch 77/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0198 - mae: 0.0198 - val_loss: 0.0125 - val_mae: 0.0125\n", "Epoch 78/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0197 - mae: 0.0197 - val_loss: 0.0117 - val_mae: 0.0117\n", "Epoch 79/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0193 - mae: 0.0193 - val_loss: 0.0081 - val_mae: 0.0081\n", "Epoch 80/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0190 - mae: 0.0190 - val_loss: 0.0110 - val_mae: 0.0110\n", "Epoch 81/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0194 - mae: 0.0194 - val_loss: 0.0111 - val_mae: 0.0111\n", "Epoch 82/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0185 - mae: 0.0185 - val_loss: 0.0089 - val_mae: 0.0089\n", "Epoch 83/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0191 - mae: 0.0191 - val_loss: 0.0096 - val_mae: 0.0096\n", "Epoch 84/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0198 - mae: 0.0198 - val_loss: 0.0130 - val_mae: 0.0130\n", "Epoch 85/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0192 - mae: 0.0192 - val_loss: 0.0103 - val_mae: 0.0103\n", "Epoch 86/100\n", "17/17 [==============================] - 0s 8ms/step - loss: 0.0188 - mae: 0.0188 - val_loss: 0.0104 - val_mae: 0.0104\n", "Epoch 87/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0191 - mae: 0.0191 - val_loss: 0.0106 - val_mae: 0.0106\n", "Epoch 88/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0200 - mae: 0.0200 - val_loss: 0.0096 - val_mae: 0.0096\n", "Epoch 89/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0189 - mae: 0.0189 - val_loss: 0.0098 - val_mae: 0.0098\n", "Epoch 90/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0191 - mae: 0.0191 - val_loss: 0.0119 - val_mae: 0.0119\n", "Epoch 91/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0191 - mae: 0.0191 - val_loss: 0.0096 - val_mae: 0.0096\n", "Epoch 92/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0187 - mae: 0.0187 - val_loss: 0.0137 - val_mae: 0.0137\n", "Epoch 93/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0196 - mae: 0.0196 - val_loss: 0.0127 - val_mae: 0.0127\n", "Epoch 94/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0203 - mae: 0.0203 - val_loss: 0.0080 - val_mae: 0.0080\n", "Epoch 95/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0187 - mae: 0.0187 - val_loss: 0.0102 - val_mae: 0.0102\n", "Epoch 96/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0190 - mae: 0.0190 - val_loss: 0.0156 - val_mae: 0.0156\n", "Epoch 97/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0198 - mae: 0.0198 - val_loss: 0.0117 - val_mae: 0.0117\n", "Epoch 98/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0181 - mae: 0.0181 - val_loss: 0.0106 - val_mae: 0.0106\n", "Epoch 99/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0188 - mae: 0.0188 - val_loss: 0.0091 - val_mae: 0.0091\n", "Epoch 100/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0188 - mae: 0.0188 - val_loss: 0.0091 - val_mae: 0.0091\n", "WARNING:tensorflow:5 out of the last 13 calls to .predict_function at 0x7f0114293050> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for more details.\n", "MSE: 4.1E-04, RMSE: 0.02, MAE: 0.012, MAPE: 4.01 %, R_2: 0.478\n", "Epoch 1/100\n", "17/17 [==============================] - 4s 60ms/step - loss: 0.0187 - mae: 0.0187 - val_loss: 0.0092 - val_mae: 0.0092\n", "Epoch 2/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0199 - mae: 0.0199 - val_loss: 0.0086 - val_mae: 0.0086\n", "Epoch 3/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0189 - mae: 0.0189 - val_loss: 0.0100 - val_mae: 0.0100\n", "Epoch 4/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0185 - mae: 0.0185 - val_loss: 0.0089 - val_mae: 0.0089\n", "Epoch 5/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0191 - mae: 0.0191 - val_loss: 0.0119 - val_mae: 0.0119\n", "Epoch 6/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0176 - mae: 0.0176 - val_loss: 0.0056 - val_mae: 0.0056\n", "Epoch 7/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0186 - mae: 0.0186 - val_loss: 0.0064 - val_mae: 0.0064\n", "Epoch 8/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0187 - mae: 0.0187 - val_loss: 0.0070 - val_mae: 0.0070\n", "Epoch 9/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0170 - mae: 0.0170 - val_loss: 0.0074 - val_mae: 0.0074\n", "Epoch 10/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0182 - mae: 0.0182 - val_loss: 0.0085 - val_mae: 0.0085\n", "Epoch 11/100\n", "17/17 [==============================] - 0s 18ms/step - loss: 0.0168 - mae: 0.0168 - val_loss: 0.0106 - val_mae: 0.0106\n", "Epoch 12/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0197 - mae: 0.0197 - val_loss: 0.0083 - val_mae: 0.0083\n", "Epoch 13/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0184 - mae: 0.0184 - val_loss: 0.0107 - val_mae: 0.0107\n", "Epoch 14/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0176 - mae: 0.0176 - val_loss: 0.0078 - val_mae: 0.0078\n", "Epoch 15/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0185 - mae: 0.0185 - val_loss: 0.0073 - val_mae: 0.0073\n", "Epoch 16/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0186 - mae: 0.0186 - val_loss: 0.0094 - val_mae: 0.0094\n", "Epoch 17/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0188 - mae: 0.0188 - val_loss: 0.0083 - val_mae: 0.0083\n", "Epoch 18/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0183 - mae: 0.0183 - val_loss: 0.0106 - val_mae: 0.0106\n", "Epoch 19/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0187 - mae: 0.0187 - val_loss: 0.0088 - val_mae: 0.0088\n", "Epoch 20/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0183 - mae: 0.0183 - val_loss: 0.0107 - val_mae: 0.0107\n", "Epoch 21/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0178 - mae: 0.0178 - val_loss: 0.0073 - val_mae: 0.0073\n", "Epoch 22/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0189 - mae: 0.0189 - val_loss: 0.0073 - val_mae: 0.0073\n", "Epoch 23/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0191 - mae: 0.0191 - val_loss: 0.0092 - val_mae: 0.0092\n", "Epoch 24/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0194 - mae: 0.0194 - val_loss: 0.0057 - val_mae: 0.0057\n", "Epoch 25/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0177 - mae: 0.0177 - val_loss: 0.0091 - val_mae: 0.0091\n", "Epoch 26/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0179 - mae: 0.0179 - val_loss: 0.0085 - val_mae: 0.0085\n", "Epoch 27/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0181 - mae: 0.0181 - val_loss: 0.0081 - val_mae: 0.0081\n", "Epoch 28/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0196 - mae: 0.0196 - val_loss: 0.0075 - val_mae: 0.0075\n", "Epoch 29/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0185 - mae: 0.0185 - val_loss: 0.0084 - val_mae: 0.0084\n", "Epoch 30/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0186 - mae: 0.0186 - val_loss: 0.0089 - val_mae: 0.0089\n", "Epoch 31/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0178 - mae: 0.0178 - val_loss: 0.0100 - val_mae: 0.0100\n", "Epoch 32/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0181 - mae: 0.0181 - val_loss: 0.0113 - val_mae: 0.0113\n", "Epoch 33/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0177 - mae: 0.0177 - val_loss: 0.0067 - val_mae: 0.0067\n", "Epoch 34/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0180 - mae: 0.0180 - val_loss: 0.0098 - val_mae: 0.0098\n", "Epoch 35/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0185 - mae: 0.0185 - val_loss: 0.0087 - val_mae: 0.0087\n", "Epoch 36/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0185 - mae: 0.0185 - val_loss: 0.0091 - val_mae: 0.0091\n", "Epoch 37/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0188 - mae: 0.0188 - val_loss: 0.0067 - val_mae: 0.0067\n", "Epoch 38/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0177 - mae: 0.0177 - val_loss: 0.0112 - val_mae: 0.0112\n", "Epoch 39/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0200 - mae: 0.0200 - val_loss: 0.0098 - val_mae: 0.0098\n", "Epoch 40/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0176 - mae: 0.0176 - val_loss: 0.0079 - val_mae: 0.0079\n", "Epoch 41/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0184 - mae: 0.0184 - val_loss: 0.0073 - val_mae: 0.0073\n", "Epoch 42/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0180 - mae: 0.0180 - val_loss: 0.0082 - val_mae: 0.0082\n", "Epoch 43/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0183 - mae: 0.0183 - val_loss: 0.0076 - val_mae: 0.0076\n", "Epoch 44/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0188 - mae: 0.0188 - val_loss: 0.0089 - val_mae: 0.0089\n", "Epoch 45/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0184 - mae: 0.0184 - val_loss: 0.0094 - val_mae: 0.0094\n", "Epoch 46/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0183 - mae: 0.0183 - val_loss: 0.0081 - val_mae: 0.0081\n", "Epoch 47/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0182 - mae: 0.0182 - val_loss: 0.0066 - val_mae: 0.0066\n", "Epoch 48/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0183 - mae: 0.0183 - val_loss: 0.0079 - val_mae: 0.0079\n", "Epoch 49/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0181 - mae: 0.0181 - val_loss: 0.0104 - val_mae: 0.0104\n", "Epoch 50/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0173 - mae: 0.0173 - val_loss: 0.0098 - val_mae: 0.0098\n", "Epoch 51/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0182 - mae: 0.0182 - val_loss: 0.0069 - val_mae: 0.0069\n", "Epoch 52/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0191 - mae: 0.0191 - val_loss: 0.0060 - val_mae: 0.0060\n", "Epoch 53/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0179 - mae: 0.0179 - val_loss: 0.0084 - val_mae: 0.0084\n", "Epoch 54/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0184 - mae: 0.0184 - val_loss: 0.0070 - val_mae: 0.0070\n", "Epoch 55/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0190 - mae: 0.0190 - val_loss: 0.0099 - val_mae: 0.0099\n", "Epoch 56/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0170 - mae: 0.0170 - val_loss: 0.0088 - val_mae: 0.0088\n", "Epoch 57/100\n", "17/17 [==============================] - 0s 12ms/step - loss: 0.0187 - mae: 0.0187 - val_loss: 0.0079 - val_mae: 0.0079\n", "Epoch 58/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0181 - mae: 0.0181 - val_loss: 0.0072 - val_mae: 0.0072\n", "Epoch 59/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0178 - mae: 0.0178 - val_loss: 0.0085 - val_mae: 0.0085\n", "Epoch 60/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0178 - mae: 0.0178 - val_loss: 0.0063 - val_mae: 0.0063\n", "Epoch 61/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0188 - mae: 0.0188 - val_loss: 0.0073 - val_mae: 0.0073\n", "Epoch 62/100\n", "17/17 [==============================] - 0s 8ms/step - loss: 0.0175 - mae: 0.0175 - val_loss: 0.0099 - val_mae: 0.0099\n", "Epoch 63/100\n", "17/17 [==============================] - 0s 7ms/step - loss: 0.0177 - mae: 0.0177 - val_loss: 0.0080 - val_mae: 0.0080\n", "Epoch 64/100\n", "17/17 [==============================] - 0s 6ms/step - loss: 0.0178 - mae: 0.0178 - val_loss: 0.0074 - val_mae: 0.0074\n", "Epoch 65/100\n", "17/17 [==============================] - 0s 7ms/step - loss: 0.0171 - mae: 0.0171 - val_loss: 0.0116 - val_mae: 0.0116\n", "Epoch 66/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0179 - mae: 0.0179 - val_loss: 0.0112 - val_mae: 0.0112\n", "Epoch 67/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0183 - mae: 0.0183 - val_loss: 0.0067 - val_mae: 0.0067\n", "Epoch 68/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0183 - mae: 0.0183 - val_loss: 0.0071 - val_mae: 0.0071\n", "Epoch 69/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0180 - mae: 0.0180 - val_loss: 0.0128 - val_mae: 0.0128\n", "Epoch 70/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0186 - mae: 0.0186 - val_loss: 0.0106 - val_mae: 0.0106\n", "Epoch 71/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0192 - mae: 0.0192 - val_loss: 0.0062 - val_mae: 0.0062\n", "Epoch 72/100\n", "17/17 [==============================] - 0s 9ms/step - loss: 0.0178 - mae: 0.0178 - val_loss: 0.0111 - val_mae: 0.0111\n", "Epoch 73/100\n", "17/17 [==============================] - 0s 8ms/step - loss: 0.0186 - mae: 0.0186 - val_loss: 0.0089 - val_mae: 0.0089\n", "Epoch 74/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0178 - mae: 0.0178 - val_loss: 0.0073 - val_mae: 0.0073\n", "Epoch 75/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0171 - mae: 0.0171 - val_loss: 0.0071 - val_mae: 0.0071\n", "Epoch 76/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0184 - mae: 0.0184 - val_loss: 0.0092 - val_mae: 0.0092\n", "Epoch 77/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0175 - mae: 0.0175 - val_loss: 0.0095 - val_mae: 0.0095\n", "Epoch 78/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0177 - mae: 0.0177 - val_loss: 0.0091 - val_mae: 0.0091\n", "Epoch 79/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0185 - mae: 0.0185 - val_loss: 0.0067 - val_mae: 0.0067\n", "Epoch 80/100\n", "17/17 [==============================] - 0s 17ms/step - loss: 0.0192 - mae: 0.0192 - val_loss: 0.0078 - val_mae: 0.0078\n", "Epoch 81/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0195 - mae: 0.0195 - val_loss: 0.0130 - val_mae: 0.0130\n", "Epoch 82/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0176 - mae: 0.0176 - val_loss: 0.0096 - val_mae: 0.0096\n", "Epoch 83/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0182 - mae: 0.0182 - val_loss: 0.0059 - val_mae: 0.0059\n", "Epoch 84/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0178 - mae: 0.0178 - val_loss: 0.0065 - val_mae: 0.0065\n", "Epoch 85/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0185 - mae: 0.0185 - val_loss: 0.0069 - val_mae: 0.0069\n", "Epoch 86/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0179 - mae: 0.0179 - val_loss: 0.0075 - val_mae: 0.0075\n", "Epoch 87/100\n", "17/17 [==============================] - 0s 15ms/step - loss: 0.0174 - mae: 0.0174 - val_loss: 0.0099 - val_mae: 0.0099\n", "Epoch 88/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0172 - mae: 0.0172 - val_loss: 0.0066 - val_mae: 0.0066\n", "Epoch 89/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0183 - mae: 0.0183 - val_loss: 0.0088 - val_mae: 0.0088\n", "Epoch 90/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0182 - mae: 0.0182 - val_loss: 0.0060 - val_mae: 0.0060\n", "Epoch 91/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0180 - mae: 0.0180 - val_loss: 0.0072 - val_mae: 0.0072\n", "Epoch 92/100\n", "17/17 [==============================] - 0s 13ms/step - loss: 0.0171 - mae: 0.0171 - val_loss: 0.0081 - val_mae: 0.0081\n", "Epoch 93/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0194 - mae: 0.0194 - val_loss: 0.0085 - val_mae: 0.0085\n", "Epoch 94/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0168 - mae: 0.0168 - val_loss: 0.0093 - val_mae: 0.0093\n", "Epoch 95/100\n", "17/17 [==============================] - 0s 11ms/step - loss: 0.0172 - mae: 0.0172 - val_loss: 0.0078 - val_mae: 0.0078\n", "Epoch 96/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0180 - mae: 0.0180 - val_loss: 0.0080 - val_mae: 0.0080\n", "Epoch 97/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0180 - mae: 0.0180 - val_loss: 0.0102 - val_mae: 0.0102\n", "Epoch 98/100\n", "17/17 [==============================] - 0s 10ms/step - loss: 0.0176 - mae: 0.0176 - val_loss: 0.0122 - val_mae: 0.0122\n", "Epoch 99/100\n", "17/17 [==============================] - 0s 14ms/step - loss: 0.0174 - mae: 0.0174 - val_loss: 0.0109 - val_mae: 0.0109\n", "Epoch 100/100\n", "17/17 [==============================] - 0s 16ms/step - loss: 0.0176 - mae: 0.0176 - val_loss: 0.0068 - val_mae: 0.0068\n", "MSE: 1.5E-04, RMSE: 0.012, MAE: 0.009, MAPE: 3.07 %, R_2: 0.922\n" ] } ], "source": [ "eva_list = list()\n", "for (train_index, test_index) in kf.split(use_data):\n", " train = use_data.loc[train_index]\n", " test = use_data.loc[test_index]\n", " train, valid = train_test_split(train, test_size=0.15, random_state=666)\n", " X_train, Y_train = train[feature_cols], train['CO2_em_air']\n", " X_valid, Y_valid = valid[feature_cols], valid['CO2_em_air']\n", " X_test, Y_test = valid[feature_cols], valid['CO2_em_air']\n", " model.compile(optimizer=opt, loss=tf.keras.losses.MAE, metrics=['mae'])\n", " model_history = model.fit(\n", " {'input': np.expand_dims(X_train.values, axis=1)},\n", " {\n", " 'out': Y_train.values,\n", " },\n", " validation_data=(np.expand_dims(X_valid[feature_cols].values, axis=1), Y_valid.values),\n", " epochs=100, batch_size=32, verbose=1)\n", "\n", " y_pred = np.expm1(model.predict(np.expand_dims(X_test[feature_cols].values, axis=1)))\n", " y_true = np.expm1(Y_test.values)\n", " MSE = mean_squared_error(y_true, y_pred)\n", " RMSE = np.sqrt(mean_squared_error(y_true, y_pred))\n", " MAE = mean_absolute_error(y_true, y_pred)\n", " MAPE = mean_absolute_percentage_error(y_true, y_pred)\n", " R_2 = r2_score(y_true, y_pred)\n", " print('MSE:', format(MSE, '.1E'), end=', ')\n", " print('RMSE:', round(RMSE, 3), end=', ')\n", " print('MAE:', round(MAE, 3), end=', ')\n", " print('MAPE:', round(MAPE*100, 2), '%', end=', ')\n", " print('R_2:', round(R_2, 3)) #R方为负就说明拟合效果比平均值差\n", " if R_2 >= 0.9:\n", " eva_list.append([MSE, RMSE, MAE, MAPE, R_2])\n", " break\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "py37", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.13" }, "vscode": { "interpreter": { "hash": "993bd31d5df1020fab369d79a34ff0a2a159e1798f3e25d3ad4b7751d38184c9" } } }, "nbformat": 4, "nbformat_minor": 0 }