51 lines
1.2 KiB
Python
51 lines
1.2 KiB
Python
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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(100 * (pred - true) / (true +1e-8)))
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def MSPE(pred, true):
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return np.mean(np.square((pred - true) / (true + 1e-8)))
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def SMAPE(pred, true):
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return np.mean(200 * np.abs(pred - true) / (np.abs(pred) + np.abs(true) + 1e-8))
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# return np.mean(200 * np.abs(pred - true) / (pred + true + 1e-8))
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def ND(pred, true):
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return np.mean(np.abs(true - pred)) / np.mean(np.abs(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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smape = SMAPE(pred, true)
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nd = ND(pred, true)
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return mae, mse, rmse, mape, mspe, smape, nd
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