Principal Component Analysis
In this, we will do a very short tour of PCA, mainly its computation. The scikit guide has some advanced details on the actual usage of PCA. Basic idea The goal of principal component analysis is to identify an orthogonal basis along which data points are spread out the most. For example, imagine a rugby ball mid-air. It’s tilted a little along some axis. Given a bag of 3-dimensional points (aka point-cloud) that comprise the shape of the rugby ball at this very mid-air position and orientation, PCA will identify the three orthogonal vectors that best represent the spread of the points....