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The Statistical Learning Framework
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Classroom Contents
Nearest Neighbors I
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- 1 Intro
- 2 Talk Outline
- 3 k Nearest Neighbors
- 4 The Metric Space
- 5 Tutorial Outline
- 6 NN Regression Setting
- 7 Universality
- 8 More Formally...
- 9 Intuition: Universal Consistency
- 10 Convergence Rates
- 11 k-NN Distances
- 12 From Distances to Rates
- 13 Bias-Variance Decomposition
- 14 Bounding Bias and Variance
- 15 Integrating across the space
- 16 Nearest Neighbor Classification
- 17 The Statistical Learning Framework
- 18 The Bayes Optimal Classifier
- 19 Consistency of I-NN
- 20 Consistency under Continuity
- 21 Proof Intuition
- 22 Universal Consistency in Metric Spaces
- 23 Main Idea in Prior Analysis
- 24 A Motivating Example
- 25 Effective Interiors and Boundaries
- 26 Convergence Rate Theorem
- 27 A Better Smoothness Condition
- 28 Smoothness Bounds
