Examining Hierarchy and Granularity of Classifiers in Compatibility-based Classifier Personalization.
Trang Thuy VuKaori FujinamiPublished in: GCCE (2019)
Keyphrases
- linear classifiers
- training data
- individual classifiers
- multiple classifiers
- classifier systems
- classifier combination
- svm classifier
- probabilistic classifiers
- feature set
- decision trees
- nearest neighbor classifier
- k nearest neighbour
- training set
- combining classifiers
- classifier training
- support vector
- classification rate
- optimum path forest
- higher classification accuracy
- decision boundary
- learning classifier systems
- classifier ensemble
- accurate classifiers
- classification decisions
- decision tree classifiers
- training instances
- classification process
- classification method
- ensemble learning
- rule based classifier
- associative classifiers
- training samples
- ensemble classifier
- kernel classifiers
- classification algorithm
- training examples
- binary classifiers
- nearest neighbor classifiers
- multi category
- unseen data
- final classification
- feature selection
- majority vote
- class labels
- extracted features
- text classifiers
- neural classifier
- supervised classification
- weak classifiers
- labeled training data
- highest accuracy
- majority voting
- bayesian classifier
- multiclass classification
- discriminative classifiers
- fold cross validation
- naive bayes classifier
- learning algorithm
- multiple classifier systems
- classification models
- knn
- roc curve
- supervised classifiers
- support vector machine
- hierarchical structure
- bayes classifier
- naive bayes
- correctly classified
- class probabilities
- multi class
- adaboost algorithm
- feature extraction
- sufficient training data
- train a support vector machine
- confusion matrix
- multi label classification
- supervised learning
- classification accuracy
- active learning
- recommender systems