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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