Dynamic Sampling Approach to Training Neural Networks for Multiclass Imbalance Classification.
Minlong LinKe TangXin YaoPublished in: IEEE Trans. Neural Networks Learn. Syst. (2013)
Keyphrases
- multi class
- multiclass classification
- support vector machine
- neural network
- training process
- multiclass svm
- multi class classification
- cost sensitive classification
- multiple classes
- multiclass problems
- binary classifiers
- cost sensitive
- multi class classifier
- binary and multi class
- multiclass support vector machines
- pattern recognition
- binary classification problems
- error correcting output codes
- feature selection
- class imbalance
- supervised learning
- single class
- binary classification
- training samples
- training set
- support vector
- multi class boosting
- kernel fisher
- classification accuracy
- cost sensitive learning
- machine learning
- feature space
- pairwise
- artificial neural networks
- feature vectors
- svm classifier
- multi class problems
- decision trees
- generalization ability
- multi task
- sampling methods
- multi label classification
- high dimensionality
- perceptron algorithm
- minority class
- class distribution
- machine learning algorithms
- text classification
- image classification
- base classifiers
- multiclass learning
- training data