Multiple Kernel Learning With Minority Oversampling for Classifying Imbalanced Data.
Ling WangHongqiao WangGuangyuan FuPublished in: IEEE Access (2021)
Keyphrases
- multiple kernel learning
- imbalanced data
- minority class
- majority class
- class imbalance
- binary classification
- class distribution
- feature selection
- support vector machine
- linear combination
- decision boundary
- classification error
- nearest neighbour
- kernel methods
- original data
- cost sensitive learning
- support vectors
- kernel function
- sampling methods
- active learning
- training set
- cost sensitive
- training dataset
- learning problems
- multi task
- misclassification costs
- linear regression
- semi supervised learning
- ensemble learning
- training data
- ensemble methods
- text categorization
- learning models
- svm classifier
- high dimensionality
- unsupervised learning
- base learners
- model selection
- classification accuracy
- feature vectors
- feature extraction