User guide

• 1. EigenPro for Regression and Classification
• 2. Clustering with KMedoids, CLARA and Common-nearest-neighbors
  • 2.1. K-Medoids
  • 2.2. CLARA
  • 2.3. Common-nearest-neighbors clustering
• 3. Robust algorithms for Regression, Classification and Clustering
  • 3.1. What is an outlier ?
  • 3.2. Robust estimation with robust weighting
  • 3.3. Robust estimation in practice
    • 3.3.1. The algorithm
    • 3.3.2. Comparison with other robust estimators
    • 3.3.3. Speed and limits of the algorithm
• 4. Kernel map approximation for faster kernel methods