A Novel Multi-class Classification Architecture Combining Population-based Sampling and Multi-expert Classifier for Imbalanced Data.
Haochen JiangZiqi WeiLin LiuXiulong YuanJun ChenPublished in: SMC (2021)
Keyphrases
- imbalanced data
- multi class classification
- support vector machine
- multi class
- support vector
- binary classification
- binary classifiers
- svm classifier
- feature selection
- minority class
- ensemble classifier
- classification models
- ensemble methods
- class imbalance
- sampling methods
- class distribution
- decision trees
- ensemble learning
- decision boundary
- training data
- base classifiers
- cost sensitive learning
- linear classifiers
- random forest
- classification algorithm
- multi task learning
- cost sensitive
- feature set
- training set
- training samples
- nearest neighbour
- base learners
- feature space
- machine learning
- classification error
- data sets
- learning problems
- class labels
- prediction accuracy
- kernel function
- support vector machine svm
- classification accuracy
- learning algorithm