scikit-learn : Machine Learning Simplified

Performing Principal Component Analysis

There are several terms that we must define before discussing how principal component analysis works.

Variance, Covariance, and Covariance Matrices

Recall that variance is a measure of how a set of values are spread out. Variance is calculated as the average of the squared differences of the values and mean of the values, as per the following equation:

Covariance is a measure of how much two variables change together; it is a measure of the strength of the correlation between two sets of variables. If the covariance of two variables is zero, the variables are uncorrelated. Note that uncorrelated variables are ...