Principal Component Analysis (PCA)

Principal Component Analysis (PCA): A Physically Intuitive Mathematical Introduction

The principal component analysis (PCA) involves rotating a cloud of data points in Euclidean space such that the variance is maximal along the first axis, the so-called first principal component. The principal axis theorem ensures that the data can be rotated in such away. In mathematical terms, the PCA involves finding an orthogonal linear coordinate transformation or, more generally, a new basis.

The mathematics behind …

ai analysis data science julialang machine learning physics