Cost-sensitive boosting algorithms: Do we really need them?
Nikolaos NikolaouNarayanan Unny EdakunniMeelis KullPeter A. FlachGavin BrownPublished in: Mach. Learn. (2016)
Keyphrases
- feature selection
- boosting algorithms
- cost sensitive
- multi class
- naive bayes
- support vector machine
- binary classification
- misclassification costs
- cost sensitive learning
- text classification
- class imbalance
- active learning
- class distribution
- machine learning
- support vector
- base classifiers
- multi class classification
- data sets
- training error
- cost sensitive boosting
- markov random field
- upper bound
- high dimensional
- pairwise
- learning algorithm