Mastering Machine Learning with scikit-learn - Second Edition

Performing PCA

Let's use PCA to reduce the following two-dimensional dataset to one dimension:

x1	x2
0.9	1
2.4	2.6
1.2	1.7
0.5	0.7
0.3	0.7
1.8	1.4
0.5	0.6
0.3	0.6
2.5	2.6
1.3	1.1

The first step of PCA is to subtract the mean of each explanatory variable from each observation:

x1	x2
0.9 - 1.17 = -0.27	1 - 1.3 = -0.3
2.4 - 1.17 = 1.23	2.6 - 1.3 = 1.3
1.2 - 1.17 = 0.03	1.7 - 1.3 = 0.4
0.5 - 1.17 = -0.67	-0.7 - 1.3 = 0.6
0.3 - 1.17 = -0.87	-0.7 - 1.3 = 0.6
1.8 - 1.17 = 0.63	1.4 - 1.3 = 0.1
0.5 - 1.17 = -0.67	0.6 - 1.3 = -0.7
0.3 - 1.17 = -0.87	0.6 - 1.3 = -0.7
2.5 - 1.17 = 1.33	2.6 - 1.3 = 1.3
1.3 - 1.17 = 0.13 ...