08. Video: PCA Properties

Principal Component Properties

There are two main properties of principal components:

1. They retain the most amount of information in the dataset. In this video, you saw that retaining the most information in the dataset meant finding a line that reduced the distances of the points to the component across all the points (same as in regression!).

2. The created components are orthogonal to one another. So far we have been mostly focused on what the first component of a dataset would look like. However, when there are many components, the additional components will all be orthogonal to one another. Depending on how the components are used, there are benefits to having orthogonal components. In regression, we often would like independent features, so using the components in regression now guarantees this.

This is a great post answering a number of common questions on PCA.