Reinforcement Learning as Classification: Leveraging Modern Classifiers.
Michail G. LagoudakisRonald ParrPublished in: ICML (2003)
Keyphrases
- reinforcement learning
- classification systems
- support vector
- classification algorithm
- classification models
- decision trees
- supervised classification
- training set
- class labels
- feature selection
- probabilistic classifiers
- pattern recognition
- classification accuracy
- improves the classification accuracy
- classification method
- classification process
- multiclass classification
- classification rate
- support vector machine classifiers
- training samples
- k nearest neighbour
- training data
- binary classifiers
- classification procedure
- classification decisions
- machine learning methods
- rule based classifier
- svm classifier
- machine learning algorithms
- learning algorithm
- multi category
- decision boundary
- decision tree classifiers
- multiple classifiers
- accurate classification
- nearest neighbor classifier
- machine learning
- higher classification accuracy
- individual classifiers
- feature set
- support vector machine
- feature extraction
- ensemble classifier
- image classification
- multiple classifier systems
- data stream classification
- correctly classified
- majority voting
- training examples
- naive bayes
- support vector machine svm
- associative classifiers
- final classification
- accurate classifiers
- classifier combination
- classifier ensemble
- nearest neighbour
- knn
- imbalanced data sets
- discriminant functions
- state space
- roc analysis
- feature vectors
- optimal policy