A Guide to Principal Component Analysis

The process of normalization, where x_new is the normalized vector of x_old.
Building a covariance matrix.
The covariance between two variables.
The diagram above shows a set of data with two variables. The first principal component follows the direction of maximum variance, and the second principal component is the direction of maximum variance that is orthogonal to the first. (Source: Analytics Vidhya)
The loss of information due to PCA compared to the original information.
An example of how principal component summarizes the variance in data. (Source: Stackoverflow)

--

--

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store