Category
page 1Model selection
cross-validation
statistical model validation technique
Akaike information criterion
statistics
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
Bayes factor
ratio of the marginal likelihood of two statistical models
Bayesian information criterion
statistical concept
hyperparameter
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
learning rate
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
double descent
concept in machine learning