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MattLowrieDS/compute_class_weight

Created January 6, 2021 03:07
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Example using sklearn compute_class_weight()
Raw
compute_class_weight
from sklearn.utils.class_weight import compute_class_weight
pass_results = plays_df.loc[plays_df['passResult'].isin(category_lookup.keys()), 'passResult']
all_labels = pass_results.apply(lambda lbl: category_lookup[lbl])
# Create class weights to counter-balance classification during training
y = np.stack(all_labels).argmax(axis=1)
classes = np.unique(y)
weights = compute_class_weight('balanced', classes=classes, y=y)
class_weights = {k: v for k, v in zip(classes, weights)}
print('Class weights:', class_weights)
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