Combining Multiple Statistical Classifiers to Improve the Accuracy of Task Classification.
Wei-Lin WuRuzhan LuFeng GaoYan YuanPublished in: CICLing (2005)
Keyphrases
- combining multiple
- individual classifiers
- multiple classifiers
- combining classifiers
- classifier combination
- classification accuracy
- fusion methods
- decision trees
- support vector
- ensemble learning
- improving classification accuracy
- classification rate
- cluster ensemble
- classification method
- high classification accuracy
- higher classification accuracy
- classification systems
- roc curve
- majority voting
- fold cross validation
- confusion matrix
- binary classification
- classification algorithm
- class labels
- classification models
- training data
- correctly classified
- unseen data
- roc analysis
- training samples
- naive bayes
- classifier ensemble
- svm classifier
- fusion framework
- feature set
- supervised learning
- pattern recognition
- cost sensitive
- machine learning
- feature selection