PAC-learning in the presence of one-sided classification noise.
Hans Ulrich SimonPublished in: Ann. Math. Artif. Intell. (2014)
Keyphrases
- classification noise
- pac learning
- uniform distribution
- computational learning theory
- learning theory
- sample complexity
- sample size
- learning problems
- attribute noise
- target concept
- vc dimension
- agnostic learning
- membership queries
- concept classes
- statistical queries
- decision lists
- decision trees
- text classification
- learning algorithm
- concept learning
- text categorization
- noise tolerant
- mistake bound
- special case
- training data