Principal Component Analysis — A Brief Introduction
A non-technical introduction to a widely used dimensionality reduction technique
We live in a 3 dimensional space. Things around us have a width, breadth and depth. We see the movies and paintings in 2 dimensions and certain observations just have a single dimension. Lower dimensions are easy for us to visualize. But it gets harder to think about and visualize things as the dimensions increase. Wrapping our head around a n-dimensional quantity is a huge challenge. A n-dimensional quantity is not uncommon when we are dealing with data. Wouldn’t it be nice if we could somehow squeeze our data from higher dimensions to lower dimensions without loosing much information? Lets see how can we do that.
You are a newbie in the art of wine making and wine appreciation and are trying to learn about different types of wines and classify them depending on their properties. You can use many characteristics or properties of the wine like color, its body, odor, age etc. to describe each wine.
The wine here is our object which we are trying to describe through its features. This object is being…
