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Stat 479: Machine Learning Lecture Notes
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02 knn notes
Document Outline
Nearest
Neighbor Methods
Introduction
Key concepts
Nearest Neighbor Classification In Context
Common
Use Cases of kNN
Nearest Neighbor Algorithm
Nearest Neighbor Decision Boundary
k-Nearest Neighbor
Classification and Regression
Classification
Regression
Curse of Dimensionality
Computational Complexity and the Big-O Notation
Big
O of kNN
Improving Computational Performance
Naive kNN Algorithm in Pseudocode
Data
Structures
Dimensionality Reduction
Faster Distance Metric/Heuristic
``Pruning''
Parallelizing kNN
Distance measures
Discrete
Features
Feature Weighting
Distance-weighted kNN
Improving Predictive Performance
Error Bounds
kNN
from a Bayesian Perspective
Advantages and Disadvantages of kNN
Other Forms of Instance-based Learning
Locally
Weighted Regression
Kernel Methods
kNN in Python
Resources
Assigned Reading
Further Reading
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