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gorold
40 lines
883 B
Python
40 lines
883 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 calc_metrics(pred, true):
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return {'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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