Boosting Localized Classifiers in Heterogeneous Databases.
Aleksandar LazarevicZoran ObradovicPublished in: SDM (2001)
Keyphrases
- heterogeneous databases
- ensemble learning
- weak classifiers
- randomized trees
- weak learners
- feature selection
- database
- databases
- ensemble classifier
- boosting algorithms
- improving classification accuracy
- relational databases
- boosting framework
- data sources
- decision stumps
- accurate classifiers
- majority voting
- learning algorithm
- linear classifiers
- heterogeneous data
- training data
- adaboost algorithm
- information integration
- multiple classifier systems
- boosted classifiers
- training set
- decision trees
- machine learning
- ensemble methods
- discriminative classifiers
- support vector
- information retrieval
- training samples
- feature set
- base classifiers
- data sets
- naive bayes
- object oriented
- uniform access
- data analysis