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Model selection

Known as: Model comparison 
Model selection is the task of selecting a statistical model from a set of candidate models, given data. In the simplest cases, a pre-existing set of… Expand
Wikipedia

Related topics

Related topics

39 relations
Additive modelAkaike information criterionAlgorithmic information theoryAll models are wrong
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2010
Review
2010
A survey of cross-validation procedures for model selection
Used to estimate the risk of an estimator or to perform model selection, cross-validation is a widespread strategy because of its… Expand
Highly Cited
2010
Highly Cited
2010
On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation
Model selection strategies for machine learning algorithms typically involve the numerical optimisation of an appropriate model… Expand
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Highly Cited
2006
Highly Cited
2006
On Model Selection Consistency of Lasso
Sparsity or parsimony of statistical models is crucial for their proper interpretations, as in sciences and social sciences… Expand
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Review
2003
Review
2003
Model Selection and Multimodel Inference
chemists. Commenting on the new material in the second edition (2E), which was published in 1991, Blackwood (1994) noted the… Expand
Highly Cited
2001
Highly Cited
2001
Model Selection and Model Averaging
Given a data set, you can fit thousands of models at the push of a button, but how do you choose the best? With so many candidate… Expand
Highly Cited
1998
Highly Cited
1998
Model selection and multimodel inference
The first € price and the £ and $ price are net prices, subject to local VAT. Prices indicated with * include VAT for books; the… Expand
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Highly Cited
1998
Highly Cited
1998
Regression and Time Series Model Selection
Introduction to model selection the univariate regression model the univariate autoregressive model the multivariate regression… Expand
Highly Cited
1997
Highly Cited
1997
Model selection: An integral part of inference
We argue that model selection uncertainty should be fully incorporated into statistical inference whenever estimation is… Expand
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Review
1995
Review
1995
A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection
We review accuracy estimation methods and compare the two most common methods crossvalidation and bootstrap. Recent experimental… Expand
Highly Cited
1989
Highly Cited
1989
Regression and time series model selection in small samples
SUMMARY A bias correction to the Akaike information criterion, AIC, is derived for regression and autoregressive time series… Expand
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