Data Science, Machine Learning, Pca, Big Data, Principal Component.
150 components(eigenfaces) in order to maximize the variance of the dataset. from sklearn.decomposition import PCA faces_pca = PCA(n_components=150, svd_solver=’randomized’).fit(faces.data) # Plot principal components fig, axes = plt.subplots(3, 10, figsize=(12, 4), subplot_kw={'xticks':[],