PAC Learning with Constant-Partition Classification Noise and Applications to Decision Tree Induction.
Scott E. DecaturPublished in: ICML (1997)
Keyphrases
- pac learning
- classification noise
- uniform distribution
- decision trees
- computational learning theory
- learning theory
- learning problems
- attribute noise
- sample size
- sample complexity
- concept classes
- target concept
- membership queries
- statistical queries
- mistake bound
- vc dimension
- agnostic learning
- decision lists
- theoretical analysis
- induction algorithms
- pac model
- machine learning algorithms
- multi class
- machine learning
- learning dnf
- boolean functions
- cross validation
- naive bayes
- upper bound
- learning algorithm