An Ensemble of Classifiers for coping with Recurring Contexts in Data Streams.
Ioannis KatakisGrigorios TsoumakasIoannis P. VlahavasPublished in: ECAI (2008)
Keyphrases
- data stream classification
- data streams
- concept drift
- ensemble classifier
- ensemble learning
- concept drifting
- drifting concepts
- concept drifting data streams
- mining concept drifting data streams
- data stream mining
- ensemble classification
- streaming data
- classifier ensemble
- stream data
- sliding window
- change detection
- classification algorithm
- training set
- multiple classifiers
- final classification
- anytime classification
- majority voting
- individual classifiers
- data distribution
- training data
- ensemble methods
- feature selection
- continuous queries
- trained classifiers
- weighted voting
- decision trees
- ensemble pruning
- support vector
- neural network
- accurate classifiers
- non stationary
- data sets
- combining classifiers
- ensemble members
- multi class
- diversity measures
- feature ranking
- imbalanced data
- text classification
- weak classifiers
- randomized trees
- naive bayes
- learning algorithm
- decision tree classifiers
- noisy data streams
- machine learning algorithms