Mining Several Data Bases With an Ensemble of Classifiers
Seppo PuuronenVagan Y. TerziyanAlexander LogvinovskyPublished in: DEXA (1999)
Keyphrases
- ensemble classifier
- ensemble learning
- multiple classifiers
- majority voting
- training data
- databases
- classifier ensemble
- training set
- ensemble pruning
- knowledge discovery
- randomized trees
- final classification
- ensemble classification
- combining classifiers
- ensemble methods
- support vector
- decision trees
- text mining
- concept drifting
- decision tree classifiers
- accurate classifiers
- multiple classifier systems
- individual classifiers
- feature selection
- weighted voting
- ensemble members
- class label noise
- neural network
- diversity measures
- classification algorithm
- association rule mining
- mining concept drifting data streams
- one class support vector machines
- trained classifiers
- learning algorithm
- majority vote
- machine learning methods
- frequent patterns
- random forest
- concept drifting data streams
- data mining techniques
- machine learning algorithms
- pruning algorithm
- concept drift
- sequential patterns
- data sets
- classifier combination
- base classifiers
- noisy data streams
- pattern mining
- data mining
- random forests
- combining multiple
- machine learning
- weak classifiers
- database systems
- fusion methods
- feature set
- binary classification problems
- itemsets
- training samples
- text categorization
- weak learners
- imbalanced data