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