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Classroom Contents
Logistic Regression and Ensemble Learning - Bagging and Boosting - AdaBoost
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- 1 Introduction
- 2 Probability
- 3 Classification
- 4 Regression vs Classification
- 5 Ensemble Learning
- 6 Benefits of Ensemble Learning
- 7 Independent Classifiers
- 8 Pros Cons
- 9 Randomness
- 10 When does bagging work
- 11 Boosting
- 12 Strong vs Weak Learners
- 13 Basic Algorithm Training
- 14 Weighted Vote
- 15 normalizing constant
- 16 AdaBoost
- 17 Strong NonLinear Classifier
- 18 Decision Stumps
