SMOTE-Least Square Support Vector Machine for Classification of Multiclass Imbalanced Data.
Santi Wulan PurnamiRani Kemala TrapsilasiwiPublished in: ICMLC (2017)
Keyphrases
- imbalanced data
- multi class
- support vector machine
- cost sensitive
- feature selection
- class distribution
- imbalanced data sets
- base classifiers
- class imbalance
- imbalanced datasets
- classification models
- svm classifier
- multi class classification
- binary classifiers
- decision trees
- binary classification
- minority class
- ensemble classifier
- decision boundary
- pairwise
- cost sensitive learning
- linear regression
- ensemble methods
- support vector machine svm
- support vector
- training set
- machine learning
- misclassification costs
- feature vectors
- similarity measure
- linear classifiers
- generalization ability
- nearest neighbour
- kernel function
- image classification
- classification accuracy
- support vectors
- ensemble learning
- classification algorithm
- benchmark datasets
- sampling methods
- supervised learning
- feature space
- active learning