Sebastian Raschka, 2015

Python Machine Learning - Code Examples

• 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