PCA

Learn about PCA and why it's useful for data preprocessing.

Chapter Goals:

  • Learn about principal component analysis and why it's used

A. Dimensionality reduction

Most datasets contain a large number of features, some of which are redundant or not informative. For example, in a dataset of basketball statistics, the total points and points per game for a player will (most of the time) tell the same story about the player's scoring prowess.

When a dataset contains these types of correlated numeric features, we can perform ...