Machine Learning - Principal Component Analysis

Klipi teostus: Mirjam Paales 17.04.2012 5222 vaatamist Arvutiteadus

Given by Kristjan Korjus
Brief summary: I would like you to know what is PCA, how and when to use it, how to explain it to someone not familiar with the topic, how to plot and interpret the results of the analysis and how to write a nice report using the method. To sum up, I would like you to be able to get a full skillset needed to use PCA in practice.


This lecture describes the mathematical background of the PCA. Your goal is to apply PCA to the data of the richest and the biggest countries in the world and write a nice report explaining your analysis of the data.

Materials: Lecture notes, R code, Exercise, Data


  • Bishop: Pattern Recognition and Machine Learning pages 559 - 599

Complementary exercises:

Free implementations:

  • Built-in stats package in R: princomp, prcomp