Skip to search formSkip to main content
You are currently offline. Some features of the site may not work correctly.

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
Expand

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2020
Review
2020
Deep Learning for Physical-Layer 5G Wireless Techniques: Opportunities, Challenges and Solutions
The new demands for high-reliability and ultra-high capacity wireless communication have led to extensive research into 5G… Expand
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Is this relevant?
Review
2019
Review
2019
Edge Intelligence: Paving the Last Mile of Artificial Intelligence With Edge Computing
With the breakthroughs in deep learning, the recent years have witnessed a booming of artificial intelligence (AI) applications… Expand
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Is this relevant?
Review
2018
Review
2018
Exploring communities of inquiry in Massive Open Online Courses
Abstract This study presents an evaluation of the Community of Inquiry (CoI) survey instrument developed by Arbaugh et al. (2008… Expand
  • figure 1
  • table 1
  • table 2
  • figure 2
  • table 4
Is this relevant?
Review
2018
Review
2018
Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning
The correct use of model evaluation, model selection, and algorithm selection techniques is vital in academic machine learning… Expand
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Is this relevant?
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
  • figure 1
  • figure 2
  • table 1
Is this relevant?
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
Is this relevant?
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
  • figure 1.1
  • table 1.1
  • figure 1.2
  • figure 1.3
  • figure 1.4
Is this relevant?
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
Is this relevant?
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
  • figure 1
  • table 2
  • figure 2
  • figure 3
  • table 3
Is this relevant?
Highly Cited
1989
Highly Cited
1989
Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses
Using the Kullback-Leibler information criterion to measure the closeness of a model to the truth, the author proposes new… Expand
Is this relevant?
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy, Terms of Service, and Dataset License
ACCEPT & CONTINUE