Using an ensemble of classifiers for mispronunciation feedback.
Gopal AnanthakrishnanPreben WikOlov EngwallSherif M. AbdouPublished in: SLaTE (2011)
Keyphrases
- ensemble learning
- ensemble classifier
- classifier ensemble
- multiple classifiers
- ensemble pruning
- training data
- majority voting
- training set
- combining classifiers
- final classification
- class label noise
- decision trees
- majority vote
- individual classifiers
- decision tree classifiers
- randomized trees
- ensemble methods
- concept drifting data streams
- multiple classifier systems
- accurate classifiers
- weak classifiers
- feature selection
- trained classifiers
- diversity measures
- weak learners
- weighted voting
- one class support vector machines
- test set
- random forest
- pruning method
- ensemble classification
- naive bayes
- learning algorithm
- ensemble members
- classifier combination
- training examples
- classification algorithm
- support vector
- support vector machine
- random forests
- imbalanced data
- data sets
- mining concept drifting data streams
- neural network
- base classifiers
- classifier fusion
- pruning algorithm
- training samples
- classification systems
- linear classifiers
- fusion method
- generalization error
- relevance feedback
- knn
- machine learning methods
- individual features
- svm classifier
- binary classification problems