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About Foundations of Machine Learning: Courant Institute and Google Research
t are close to 1/2, the margin is concentrated around 2T(1-ε)1/2. 1) This document summarizes a lecture on boosting machine learning algorithms. 2) It introduces the concept of weak learning and discusses how boosting algorithms like AdaBoost aim to combine weak learners to create a strong learner. 3) The AdaBoost algorithm is described in detail over multiple iterations. It maintains a distribution over training samples and focuses more on misclassified examples each round. 4) AdaBoost can be interpreted as performing coordinate descent optimization of an objective function, with the weak learners as the coordinate directions. 5) Bounds are provided
Detailed Information
| Author: | ['Anonymous Wu14iV9dq'] |
|---|---|
| Publication Year: | 2013 |
| Pages: | 42 |
| Language: | English |
| Format: | |
| Price: | FREE |
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