Handling Imbalanced Dataset in Multi-label Text Categorization using Bagging and Adaptive Boosting.
Genta Indra WinataMasayu Leylia KhodraPublished in: CoRR (2018)
Keyphrases
- text categorization
- multi label
- ensemble methods
- imbalanced datasets
- hierarchical text categorization
- random forest
- feature selection
- ensemble learning
- base learners
- multi label classification
- imbalanced data
- base classifiers
- text classification
- binary classification
- naive bayes
- random forests
- learning tasks
- cost sensitive
- knn
- decision trees
- multi label learning
- benchmark datasets
- meta learning
- prediction accuracy
- semi supervised learning
- k nearest neighbor
- weak classifiers
- data mining
- feature selections
- class distribution
- ensemble classifier
- unlabeled data
- image classification
- automatic text categorization
- machine learning
- supervised learning
- multi class
- high dimensional
- similarity measure