Instance Based Learning

This talk is based on

  1. Introduction
  2. k-Nearest Neighbor Learning
    1. When to Use K-Nearest
    2. Voronoi Diagram
    3. Behavior in the Limit
    4. Distance-Weighted kNN
    5. Curse of Dimensionality
  3. Notation
  4. Locally Weighted Regression
    1. Local Regression Descent
  5. Radial Basis Functions
    1. Radial Basis Function Networks
  6. Case-Based Reasoning
    1. CADET
    2. CADET Answers
    3. CADET vs. k-Nearest
    4. CBR Summary
  7. Lazy and Eager Learning
All in one page
Index on left