A Meta Classifier by Clustering of Classifiers.
Mohammad Iman JamnejadSajad ParvinAli HeidarzadeganMohsen MoshkiPublished in: MICAI (2) (2014)
Keyphrases
- individual classifiers
- training data
- linear classifiers
- multiple classifiers
- classifier combination
- nearest neighbor algorithm
- classifier systems
- svm classifier
- supervised classification
- combining classifiers
- support vector
- training samples
- classification rate
- class labels
- ensemble classifier
- nearest neighbor classifier
- decision trees
- feature set
- nearest neighbor classification
- rule based classifier
- probabilistic classifiers
- classification process
- training set
- classifier ensemble
- classification algorithm
- majority vote
- mixed data
- ensemble learning
- binary classifiers
- clustering algorithm
- feature selection
- decision boundary
- training examples
- k nearest neighbour
- classification method
- higher classification accuracy
- accurate classifiers
- bayesian classifier
- learning classifier systems
- naive bayes
- weak classifiers
- training instances
- bayes classifier
- neural classifier
- naive bayes classifier
- decision tree classifiers
- k means
- classifier training
- optimum path forest
- classification models
- majority voting
- multiple classifier systems
- highest accuracy
- supervised learning
- kernel classifiers
- feature space
- combination of multiple classifiers
- feature reduction
- fold cross validation
- nearest neighbour
- multiclass classification
- unseen data
- text classifiers
- search results clustering
- extracted features
- lexical features
- classification accuracy
- knn
- multi class
- feature subset
- base classifiers
- support vector machine
- classification decisions
- discriminative classifiers
- sufficient training data
- associative classifiers
- train a support vector machine
- support vector machine svm