Learnability, Sample Complexity, and Hypothesis Class Complexity for Regression Models.
Soosan BeheshtiMahdi ShamsiPublished in: CoRR (2023)
Keyphrases
- regression model
- sample complexity
- vc dimension
- vapnik chervonenkis dimension
- pac learning
- pac learnability
- learning algorithm
- theoretical analysis
- uniform convergence
- learning problems
- decision lists
- upper bound
- special case
- concept class
- supervised learning
- model selection
- lower bound
- regression analysis
- generalization error
- active learning
- concept classes
- computational complexity
- function classes
- regression methods
- sample size
- training examples
- gaussian process
- linear model
- pac model
- worst case
- machine learning
- multiple linear regression
- boolean functions
- regression trees
- inductive inference
- uniform distribution
- decision problems
- pattern languages
- unsupervised learning
- irrelevant features
- high dimensional
- machine learning algorithms
- training set
- real valued functions
- data sets
- cross validation