The classification of imbalanced large data sets based on MapReduce and ensemble of ELM classifiers.
Junhai ZhaiSufang ZhangChenxi WangPublished in: Int. J. Mach. Learn. Cybern. (2017)
Keyphrases
- imbalanced data
- ensemble classifier
- final classification
- training set
- multiple classifiers
- imbalanced data sets
- classifier ensemble
- binary classification problems
- classification systems
- majority voting
- classification algorithm
- support vector
- combining classifiers
- individual classifiers
- decision trees
- ensemble classification
- multiple classifier systems
- ensemble learning
- classification rate
- feature selection
- classifier combination
- classification models
- svm classifier
- support vector machine
- concept drifting data streams
- accurate classifiers
- ensemble methods
- accurate classification
- data sets
- class labels
- training data
- decision boundary
- weak learners
- classification method
- single class
- training samples
- classification accuracy
- multi class problems
- extreme learning machines
- feature set
- class imbalance
- machine learning algorithms
- multiclass classification
- randomized trees
- decision tree classifiers
- class imbalanced
- binary classifiers
- weak classifiers
- learning algorithm
- feature extraction
- feature space
- machine learning methods
- support vector machine svm
- feature vectors
- feature ranking
- roc curve
- trained classifiers
- ensemble pruning
- supervised learning
- active learning
- machine learning
- rare class
- knn
- multi class
- text classification
- extreme learning machine
- base classifiers
- generalization ability
- support vector regression
- class distribution
- feature selection algorithms
- minority class