Sebastian Raschka, 2015

Python Machine Learning - Code Examples

## Chapter 5 - Compressing Data via Dimensionality Reduction

- Unsupervised dimensionality reduction via principal component analysis 128
  - Total and explained variance
  - Feature transformation
  - Principal component analysis in scikit-learn
- Supervised data compression via linear discriminant analysis
  - Computing the scatter matrices
  - Selecting linear discriminants for the new feature subspace
  - Projecting samples onto the new feature space
  - LDA via scikit-learn
- Using kernel principal component analysis for nonlinear mappings
  - Kernel functions and the kernel trick
  - Implementing a kernel principal component analysis in Python
    - Example 1 – separating half-moon shapes
    - Example 2 – separating concentric circles
  - Projecting new data points
  - Kernel principal component analysis in scikit-learn
- Summary