Multiclass Imbalanced Classification Using Fuzzy C-Mean and SMOTE with Fuzzy Support Vector Machine.
Ratchakoon PruengkarnKok Wai WongChun Che FungPublished in: ICONIP (5) (2017)
Keyphrases
- multi class
- fuzzy support vector machine
- binary classification problems
- multiclass classification
- class imbalance
- support vector machine
- cost sensitive
- single class
- imbalanced data sets
- cost sensitive classification
- imbalanced data
- class distribution
- binary classifiers
- multiclass problems
- fuzzy c means
- multi class classification
- multiclass support vector machines
- multiple classes
- error correcting output codes
- binary classification
- multi class problems
- imbalanced datasets
- minority class
- class imbalanced
- feature selection
- pairwise
- clustering algorithm
- cost sensitive learning
- pattern recognition
- feature vectors
- machine learning
- fuzzy clustering
- svm classifier
- active learning
- base classifiers
- cross validation
- model selection
- feature extraction
- misclassification costs
- text classification
- knn
- support vector
- image segmentation
- decision trees
- data mining