Category

Model selection

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cross-validation

statistical model validation technique

Akaike information criterion

feature selection

procedure in machine learning and statistics

bias–variance tradeoff

property of a set of predictive models whereby models with a lower bias in parameter estimation have a higher variance of the parameter estimates across samples, and vice versa

ratio of the marginal likelihood of two statistical models

Bayesian information criterion

statistical concept

in machine learning, a parameter whose value is used to control the learning process

hyperparameter optimization

choosing a set of optimal hyperparameters for a learning algorithm

tuning parameter (hyperparameter) in optimization

model selection

task of selecting a statistical model from a set of candidate models, given data. In the simplest cases, a pre-existing set of data is considered

Hannan–Quinn information criterion

Deviance information criterion

diagnostic statistic used in Bayesian model selection

learning curve in machine learning

in machine learning, function which shows the validation and training score of an estimator for varying numbers of training samples

concept in machine learning