Learning Biased SVM with Weighted Within-Class Scatter for Imbalanced Classification.
Jing-Jing ZhangPing ZhongPublished in: Neural Process. Lett. (2020)
Keyphrases
- support vector
- support vector machine svm
- feature selection
- multi class classification
- learning algorithm
- supervised learning
- structured output
- support vector machine
- classification accuracy
- learning process
- imbalanced datasets
- feature space
- histogram intersection kernel
- positive data
- single class
- unbalanced data
- learning machines
- svm classifier
- machine learning
- class labels
- training examples
- decision trees
- minimax probability machine
- positive and unlabeled examples
- feature extraction
- multi class problems
- training data
- pattern recognition
- feature vectors
- image classification
- text classification
- positive examples
- cost sensitive
- learning problems
- classification method
- multiclass classification
- binary classification problems
- kernel machines
- imbalanced data
- training set
- standard svm
- learning tasks
- imbalanced data sets
- classification algorithm
- training samples
- kernel function