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add mean bias deviation in scoring functions
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machine_learning/scoring_functions.py
Normal file → Executable file
19
machine_learning/scoring_functions.py
Normal file → Executable file
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@ -1,4 +1,4 @@
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import numpy
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import numpy as np
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""" Here I implemented the scoring functions.
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MAE, MSE, RMSE, RMSLE are included.
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@ -41,7 +41,7 @@ def rmse(predict, actual):
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actual = np.array(actual)
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difference = predict - actual
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square_diff = np.square(dfference)
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square_diff = np.square(difference)
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mean_square_diff = square_diff.mean()
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score = np.sqrt(mean_square_diff)
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return score
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@ -61,3 +61,18 @@ def rmsle(predict, actual):
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score = np.sqrt(mean_square_diff)
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return score
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#Mean Bias Deviation
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def mbd(predict, actual):
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predict = np.array(predict)
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actual = np.array(actual)
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difference = predict - actual
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numerator = np.sum(difference) / len(predict)
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denumerator = np.sum(actual) / len(predict)
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print str(numerator)
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print str(denumerator)
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score = float(numerator) / denumerator * 100
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return score
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