The PCA example has been illustrated with the handwritten digits example from scikit-learn datasets, in which handwritten digits are created from 0-9 and its respective 64 features (8 x 8 matrix) of pixel intensities. Here, the idea is to represent the original features of 64 dimensions into as few as possible:
# PCA - Principal Component Analysis >>> import matplotlib.pyplot as plt >>> from sklearn.decomposition import PCA >>> from sklearn.datasets import load_digits >>> digits = load_digits() >>> X = digits.data >>> y = digits.target >>> print (digits.data[0].reshape(8,8))
Plot the graph ...
