Empirical Bounds on Error Differences When Using Naive Bayes.
Zoë HoarePublished in: ICAPR (1) (2005)
Keyphrases
- naive bayes
- decision trees
- expected error
- classification accuracy
- logistic regression
- naive bayes classifier
- text classification
- low variance
- uci datasets
- training data
- text categorization
- cost sensitive
- classification algorithm
- upper bound
- probability estimation
- text classifiers
- feature selection
- uci data sets
- bayesian networks
- test instances
- averaged one dependence estimators
- naive bayesian classifier
- naive bayes classification
- bayesian network classifiers
- generalization error
- lower bound
- naive bayes models
- attribute independence assumption
- independence assumption
- bayesian classifier
- locally weighted
- conditional independence assumption
- training set
- augmented naive bayes