Premium Content

Principal Component Analysis

Dimensionality reduction through eigenanalysis

This chapter requires a subscription to access.

What you'll unlock:

  • 1. The Goal: Finding Principal Directions
  • 2. Covariance and the Covariance Matrix
  • 3. PCA Algorithm Step-by-Step
  • 4. Choosing the Number of Components
  • 5. PCA for Visualization
  • 6. Limitations of PCA
Subscribe to Unlock

Already have an account? Sign in