A Case Study of Applying Boosting Naive Bayes to Claim Fraud Diagnosis.
Stijn ViaeneRichard A. DerrigGuido DedenePublished in: IEEE Trans. Knowl. Data Eng. (2004)
Keyphrases
- naive bayes
- base classifiers
- decision trees
- cost sensitive
- boosted decision trees
- feature selection
- classification accuracy
- text classification
- logistic regression
- fraud detection
- text categorization
- probability estimation
- training data
- bayesian networks
- combining classifiers
- uci data sets
- bayesian classifiers
- naive bayes classifier
- classification algorithm
- test instances
- naive bayesian classifier
- naive bayes classification
- averaged one dependence estimators
- naive bayesian classification
- bayesian classifier
- uci datasets
- decision tree learning algorithms
- ensemble learning
- machine learning
- ensemble methods
- bayesian network classifiers
- random forest
- augmented naive bayes
- text classifiers
- locally weighted
- learning algorithm
- independence assumption
- probabilistic classifiers
- training set
- multi class
- information retrieval
- association rules
- prediction accuracy
- data mining
- class distribution