Book description
This self-contained introduction shows how ensemble methods are used in real-world tasks. It first presents background and terminology for readers unfamiliar with machine learning and pattern recognition. The book then covers the main algorithms and theories, including Boosting, Bagging, Random Forest, averaging and voting schemes, and diversity measures. Moving on to more advanced topics, the author explains details behind ensemble pruning and clustering ensembles. He also describes developments in semi-supervised learning, active learning, cost-sensitive learning, class-imbalance learning, and comprehensibility enhancement.
Table of contents
- Front Cover (1/3)
- Front Cover (2/3)
- Front Cover (3/3)
- Contents
- Preface (1/3)
- Preface (2/3)
- Preface (3/3)
- Notations (1/3)
- Notations (2/3)
- Notations (3/3)
- 1. Introduction (1/5)
- 1. Introduction (2/5)
- 1. Introduction (3/5)
- 1. Introduction (4/5)
- 1. Introduction (5/5)
- 2. Boosting (1/5)
- 2. Boosting (2/5)
- 2. Boosting (3/5)
- 2. Boosting (4/5)
- 2. Boosting (5/5)
- 3. Bagging (1/4)
- 3. Bagging (2/4)
- 3. Bagging (3/4)
- 3. Bagging (4/4)
- 4. Combination Methods (1/7)
- 4. Combination Methods (2/7)
- 4. Combination Methods (3/7)
- 4. Combination Methods (4/7)
- 4. Combination Methods (5/7)
- 4. Combination Methods (6/7)
- 4. Combination Methods (7/7)
- 5. Diversity (1/4)
- 5. Diversity (2/4)
- 5. Diversity (3/4)
- 5. Diversity (4/4)
- 6. Ensemble Pruning (1/4)
- 6. Ensemble Pruning (2/4)
- 6. Ensemble Pruning (3/4)
- 6. Ensemble Pruning (4/4)
- 7. Clustering Ensembles (1/5)
- 7. Clustering Ensembles (2/5)
- 7. Clustering Ensembles (3/5)
- 7. Clustering Ensembles (4/5)
- 7. Clustering Ensembles (5/5)
- 8. Advanced Topics (1/6)
- 8. Advanced Topics (2/6)
- 8. Advanced Topics (3/6)
- 8. Advanced Topics (4/6)
- 8. Advanced Topics (5/6)
- 8. Advanced Topics (6/6)
- References (1/7)
- References (2/7)
- References (3/7)
- References (4/7)
- References (5/7)
- References (6/7)
- References (7/7)
Product information
- Title: Ensemble Methods
- Author(s):
- Release date: June 2012
- Publisher(s): Chapman and Hall/CRC
- ISBN: 9781439830055
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