Novelty-organizing classifiers applied to classification and reinforcement learning: towards flexible algorithms.
Danilo Vasconcellos VargasHirotaka TakanoJunichi MurataPublished in: GECCO (Companion) (2014)
Keyphrases
- classification algorithm
- machine learning algorithms
- classification systems
- learning algorithm
- support vector
- nearest neighbor algorithm
- classification method
- machine learning methods
- feature extraction
- reinforcement learning
- feature extraction and selection
- machine learning approaches
- feature selection algorithms
- machine learning
- class labels
- feature selection
- classification models
- feature set
- decision trees
- classification schemes
- nearest neighbour
- sufficient training data
- supervised learning
- classification accuracy
- benchmark datasets
- support vector machine classifiers
- image classification
- accurate classifiers
- accurate classification
- ensemble classifier
- novelty detection
- training data
- svm classifier
- training set
- k nearest neighbour
- classification process
- support vector machine
- supervised classification
- learning problems
- classifier ensemble
- multiclass classification
- binary classification problems
- classifier combination
- multiple classifiers
- feature vectors
- classification rate
- support vector machine svm
- ensemble methods
- improves the classification accuracy
- feature space
- rule based classifier