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MattLowrieDS/smoothen_weights_technique

Created January 6, 2021 03:13
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smoothen_weights_technique
lbl_vc = feature_label_df['labels'].value_counts()
total = lbl_vc.sum()
mu = 3.0
class_weights = {}
for i, k in enumerate(lbl_vc.keys()):
w = np.log(mu * total / float(lbl_vc[k]))
class_weights[i] = w if w > 1 else 1
print(class_weights)
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