Aggregation of classifiers ensemble using local discriminatory power and quantiles.
Bartosz SwiderskiStanislaw OsowskiMichal KrukWalid BarhoumiPublished in: Expert Syst. Appl. (2016)
Keyphrases
- discriminatory power
- feature selection
- ensemble learning
- ensemble classifier
- classifier ensemble
- multiple classifiers
- ensemble pruning
- majority voting
- training data
- training set
- final classification
- recognition rate
- multiple classifier systems
- accurate classifiers
- decision tree classifiers
- classification accuracy
- feature space
- random forests
- combining classifiers
- individual classifiers
- ensemble methods
- imbalanced data
- feature ranking
- decision trees
- randomized trees
- weighted voting
- sliding window
- weak classifiers
- base classifiers
- ensemble members
- random forest
- naive bayes
- machine learning algorithms
- support vector
- feature set
- learning algorithm
- heavy hitters
- trained classifiers
- machine learning
- svm classifier
- classification models
- multi class
- binary classification
- one class support vector machines
- multiscale
- feature subset
- data streams
- color images
- class labels
- machine learning methods
- training samples
- classifier fusion
- data distribution
- pruning algorithm
- prediction accuracy