33 lines
826 B
Python
33 lines
826 B
Python
import numpy as np
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def RSE(pred, true):
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return np.sqrt(np.sum((true-pred)**2)) / np.sqrt(np.sum((true-true.mean())**2))
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def CORR(pred, true):
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u = ((true-true.mean(0))*(pred-pred.mean(0))).sum(0)
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d = np.sqrt(((true-true.mean(0))**2*(pred-pred.mean(0))**2).sum(0))
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return (u/d).mean(-1)
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def MAE(pred, true):
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return np.mean(np.abs(pred-true))
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def MSE(pred, true):
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return np.mean((pred-true)**2)
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def RMSE(pred, true):
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return np.sqrt(MSE(pred, true))
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def MAPE(pred, true):
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return np.mean(np.abs((pred - true) / true))
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def MSPE(pred, true):
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return np.mean(np.square((pred - true) / true))
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def metric(pred, true):
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mae = MAE(pred, true)
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mse = MSE(pred, true)
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rmse = RMSE(pred, true)
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mape = MAPE(pred, true)
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mspe = MSPE(pred, true)
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return mae,mse,rmse,mape,mspe |