Comparison of Bagging and Boosting Algorithms on Sample and Feature Weighting.
Satoshi ShiraiMineichi KudoAtsuyoshi NakamuraPublished in: MCS (2009)
Keyphrases
- feature weighting
- boosting algorithms
- base classifiers
- generalization error
- weak classifiers
- ensemble methods
- text categorization
- cost sensitive
- sample size
- text classification
- feature selection
- multi class
- loss function
- decision trees
- binary classification
- upper bound
- machine learning
- ensemble learning
- weak learners
- multiple features
- classification error
- active learning
- training set
- learning algorithm
- machine learning methods
- prediction accuracy
- model selection
- text mining
- relevance feedback
- learning process