Dilution (neural networks)
id:
dilution-neural-networks-164-18729536
title:
Dilution (neural networks)
text:
Dilution and dropout are regularization techniques for reducing overfitting in artificial neural networks by preventing complex co-adaptations on training data. They are an efficient way of performing model averaging with neural networks. Dilution refers to thinning weights, while dropout refers to randomly "dropping out", or omitting, units during the training process of a neural network. Both trigger the same type of regularization.
brand slug:
wiki
category slug:
encyclopedia
description:
original url:
https://en.wikipedia.org/wiki/Dilution_(neural_networks)
date created:
2015-07-27T01:35:13Z
date modified:
2024-08-29T04:06:58Z
main entity:
{"identifier":"Q25339462","url":"https://www.wikidata.org/entity/Q25339462"}
image:
{"content_url":"https://upload.wikimedia.org/wikipedia/commons/e/ed/Dropout_mechanism.png","width":1426,"height":585}
fields total:
13
integrity:
15