wehub-resource-sync
36 lines
1.1 KiB
Python
36 lines
1.1 KiB
Python
"""Normalize features"""
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import numpy as np
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def normalize(features):
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"""Normalize features.
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Normalizes input features X. Returns a normalized version of X where the mean value of
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each feature is 0 and deviation is close to 1.
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:param features: set of features.
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:return: normalized set of features.
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"""
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# Copy original array to prevent it from changes.
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features_normalized = np.copy(features).astype(float)
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# Get average values for each feature (column) in X.
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features_mean = np.mean(features, 0)
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# Calculate the standard deviation for each feature.
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features_deviation = np.std(features, 0)
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# Subtract mean values from each feature (column) of every example (row)
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# to make all features be spread around zero.
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if features.shape[0] > 1:
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features_normalized -= features_mean
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# Normalize each feature values so that all features are close to [-1:1] boundaries.
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# Also prevent division by zero error.
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features_deviation[features_deviation == 0] = 1
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features_normalized /= features_deviation
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return features_normalized, features_mean, features_deviation
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