Evaluating learning algorithms and classifiers.
Niklas LavessonPaul DavidssonPublished in: Int. J. Intell. Inf. Database Syst. (2007)
Keyphrases
- learning algorithm
- machine learning algorithms
- training data
- training examples
- training samples
- decision trees
- machine learning
- classification algorithm
- kernel classifiers
- learning problems
- feature selection
- meta learning
- learning tasks
- classification systems
- multiple classifiers
- supervised learning
- supervised learning algorithms
- accurate classifiers
- class labels
- svm classifier
- training set
- decision stumps
- classification rate
- co training
- kernel machines
- linear classifiers
- risk bounds
- machine learning methods
- test set
- naive bayes
- feature space
- decision boundary
- learning machines
- learned models
- classifier combination
- individual classifiers
- support vector machine
- text categorization
- feature set
- unlabeled data
- labeled data