Evaluation of pattern classifiers -- Testing the significance of classification efficiency using an exact probability technique.
Edgard NyssenPublished in: Pattern Recognit. Lett. (1996)
Keyphrases
- support vector
- classification systems
- classification algorithm
- classification method
- supervised classification
- decision trees
- classification models
- class membership
- classification process
- training set
- classification procedure
- classification rate
- multiclass classification
- classification accuracy
- k nearest neighbour
- accurate classification
- class labels
- svm classifier
- feature selection
- classification decisions
- rule based classifier
- improves the classification accuracy
- higher classification accuracy
- binary classifiers
- probabilistic classifiers
- training samples
- final classification
- feature set
- bayesian classifier
- classifier combination
- ensemble classifier
- optimum path forest
- pattern recognition
- class probabilities
- roc curve
- machine learning methods
- majority voting
- multiple classifier systems
- multiple classifiers
- nearest neighbor classifier
- support vector machine classifiers
- individual classifiers
- data stream classification
- test set
- image classification
- multi class
- imbalanced data sets
- decision boundary
- feature vectors
- support vector machine svm
- text classification
- training data
- accurate classifiers
- support vector machine
- discriminant functions
- sufficient training data
- multi category
- probability distribution
- combining classifiers
- decision tree classifiers
- classifier ensemble
- naive bayes classifier
- nearest neighbour
- linear classifiers
- feature space
- ensemble learning
- statistical tests
- machine learning algorithms
- training examples
- naive bayes
- knn