Ensemble classification methods with applications in R
An essential guide to two burgeoning topics in machine learning – classification trees and ensemble learning Ensemble Classification Methods with Applications in R introduces the concepts and principles of ensemble classifiers methods and includes a review of the most commonly used techniques. This...
| Other Authors: | , , |
|---|---|
| Format: | eBook |
| Published: |
Hoboken, N.J.:
Wiley
2019.
Hoboken, N.J. : 2019. |
| Edition: | 1st edition |
| Subjects: | |
| See on Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630473906719 |
Table of Contents:
- Limitation of the individual classifiers
- Ensemble classifiers methods
- Classification with individual and ensemble trees in R
- Bankrupcty prediction through ensemble trees
- Experiments with adabag in biology classification tasks
- Generalization bounds for ranking algorithms
- Classification and regression trees for analysing irrigation decisions
- Boosted rule learner and its properties
- Credit scoring with individuals and ensemble trees
- An overview of multiple classifier systems based on GAM.
