A general framework for large-scale model selection.
Marc Daniel HaunschildSebastian Aljoscha WahlBernd FreislebenWolfgang WiechertPublished in: Optim. Methods Softw. (2006)
Keyphrases
- model selection
- cross validation
- hyperparameters
- parameter estimation
- sample size
- bayesian learning
- model selection criteria
- statistical learning
- error estimation
- meta learning
- regression model
- mixture model
- gaussian process
- generalization error
- bayesian model selection
- selection criterion
- statistical inference
- motion segmentation
- variable selection
- feature selection
- machine learning
- real world
- parameter determination
- automatic model selection
- information criterion
- marginal likelihood
- hypothesis tests
- bayesian information criterion
- generalization bounds
- posterior distribution
- markov random field