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About STAT 451: Introduction To Machine Learning Lecture Notes
The document contains lecture notes on nearest neighbor methods for machine learning. It introduces the k-nearest neighbors algorithm and its applications. The k-NN algorithm stores labeled examples from the training dataset and classifies new examples based on the labels of the k closest examples. The document discusses key concepts of k-NN like lazy learning, classification and regression with k-NN, and improving computational performance. It also covers distance measures, error analysis, and advantages/disadvantages of the k-NN algorithm.
Detailed Information
| Author: | ['SHUYUAN JIA'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 22 |
| Language: | English |
| Format: | |
| Price: | FREE |
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