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1
Introduction
2
Strong and Weak Learning
3
Theorem
4
Boosting
5
Natural Ideas
6
Training Error
7
Boosting After Training Error
8
Confidence
Description:
Explore the principles of statistical learning in this lecture by Robert Schapire from Microsoft Research. Delve into the concepts of strong and weak learning, examine key theorems, and understand the fundamentals of boosting algorithms. Learn about natural ideas in machine learning, analyze training error, and discover how boosting techniques can improve model performance. Gain insights into confidence measures and their role in statistical learning approaches.

Statistical Learning - Robert Schapire, Microsoft Research

Paul G. Allen School
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