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- Early_stopping abstract "In machine learning, early stopping is a form of regularization used to avoid overfitting when training a learner with an iterative method, such as gradient descent. Such methods update the learner so as to make it better fit the training data with each iteration. Up to a point, this improves the learner's performance on data outside of the training set. Past that point, however, improving the learner's fit to the training data comes at the expense of increased generalization error. Early stopping rules provide guidance as to how many iterations can be run before the learner begins to over-fit. Early stopping rules have been employed in many different machine learning methods, with varying amounts of theoretical foundation.".
- Early_stopping wikiPageID "213214".
- Early_stopping wikiPageLength "13318".
- Early_stopping wikiPageOutDegree "33".
- Early_stopping wikiPageRevisionID "702965791".
- Early_stopping wikiPageWikiLink AdaBoost.
- Early_stopping wikiPageWikiLink Artificial_neural_network.
- Early_stopping wikiPageWikiLink Bias–variance_tradeoff.
- Early_stopping wikiPageWikiLink Boosting_(machine_learning).
- Early_stopping wikiPageWikiLink Category:Artificial_neural_networks.
- Early_stopping wikiPageWikiLink Category:Machine_learning.
- Early_stopping wikiPageWikiLink Consistency_(statistics).
- Early_stopping wikiPageWikiLink Cross-validation_(statistics).
- Early_stopping wikiPageWikiLink Generalization_error.
- Early_stopping wikiPageWikiLink Gradient_descent.
- Early_stopping wikiPageWikiLink Machine_learning.
- Early_stopping wikiPageWikiLink Neural_network_(disambiguation).
- Early_stopping wikiPageWikiLink Nonparametric_regression.
- Early_stopping wikiPageWikiLink Overfitting.
- Early_stopping wikiPageWikiLink Principal_component_regression.
- Early_stopping wikiPageWikiLink Regularization_(mathematics).
- Early_stopping wikiPageWikiLink Reproducing_kernel_Hilbert_space.
- Early_stopping wikiPageWikiLink Spectral_regularization.
- Early_stopping wikiPageWikiLink Statistical_learning_theory.
- Early_stopping wikiPageWikiLink Test_set.
- Early_stopping wikiPageWikiLink Tikhonov_regularization.
- Early_stopping wikiPageWikiLink File:Overfitting_on_Training_Set_Data.pdf.
- Early_stopping wikiPageWikiLinkText "early stopping".
- Early_stopping wikiPageUsesTemplate Template:Main.
- Early_stopping wikiPageUsesTemplate Template:Quotation.
- Early_stopping wikiPageUsesTemplate Template:Reflist.
- Early_stopping wikiPageUsesTemplate Template:Sub.
- Early_stopping subject Category:Artificial_neural_networks.
- Early_stopping subject Category:Machine_learning.
- Early_stopping hypernym Form.
- Early_stopping type Network.
- Early_stopping comment "In machine learning, early stopping is a form of regularization used to avoid overfitting when training a learner with an iterative method, such as gradient descent. Such methods update the learner so as to make it better fit the training data with each iteration. Up to a point, this improves the learner's performance on data outside of the training set. Past that point, however, improving the learner's fit to the training data comes at the expense of increased generalization error.".
- Early_stopping label "Early stopping".
- Early_stopping sameAs Q5326898.
- Early_stopping sameAs m.01f78j.
- Early_stopping sameAs Q5326898.
- Early_stopping wasDerivedFrom Early_stopping?oldid=702965791.
- Early_stopping isPrimaryTopicOf Early_stopping.