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gabriel19913/pca2.py

Created November 26, 2019 17:50
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pca2.py
from sklearn.decomposition import PCA
pca = PCA(.99, random_state = seed)
pca.fit(scaled_X)
data = pca.transform(scaled_X)
print(f'Percentual de variância explicada por cada componente: {np.round(pca.explained_variance_ratio_*100,3)}')
print(f'Percentual total de variância explicada pelas componente: {np.round(pca.explained_variance_ratio_*100,3).sum():.3f}%')
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