[jira] [Updated] (IGNITE-8668) K-fold cross validation of models
[ https://issues.apache.org/jira/browse/IGNITE-8668?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Aleksey Zinoviev updated IGNITE-8668: - Ignite Flags: Docs Required > K-fold cross validation of models > - > > Key: IGNITE-8668 > URL: https://issues.apache.org/jira/browse/IGNITE-8668 > Project: Ignite > Issue Type: New Feature > Components: ml >Reporter: Yury Babak >Assignee: Anton Dmitriev >Priority: Major > Fix For: 2.7 > > > Cross validation is a well knows approach that allows to avoid overfitting > and therefore improve model quality. K-fold cross validation is based on > splitting dataset on _k_ disjoint subsets and using _k-1_ of them as train > subset and the remaining subset for test (with all possible combinations). > The goal of this task is to implement K-fold cross validation based on an > ability to filter dataset added recently in IGNITE-8666. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-8668) K-fold cross validation of models
[ https://issues.apache.org/jira/browse/IGNITE-8668?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Dmitriy Pavlov updated IGNITE-8668: --- Fix Version/s: (was: 2.6) 2.7 > K-fold cross validation of models > - > > Key: IGNITE-8668 > URL: https://issues.apache.org/jira/browse/IGNITE-8668 > Project: Ignite > Issue Type: New Feature > Components: ml >Reporter: Yury Babak >Assignee: Anton Dmitriev >Priority: Major > Fix For: 2.7 > > > Cross validation is a well knows approach that allows to avoid overfitting > and therefore improve model quality. K-fold cross validation is based on > splitting dataset on _k_ disjoint subsets and using _k-1_ of them as train > subset and the remaining subset for test (with all possible combinations). > The goal of this task is to implement K-fold cross validation based on an > ability to filter dataset added recently in IGNITE-8666. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-8668) K-fold cross validation of models
[ https://issues.apache.org/jira/browse/IGNITE-8668?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Anton Dmitriev updated IGNITE-8668: --- Description: Cross validation is a well knows approach that allows to avoid overfitting and therefore improve model quality. K-fold cross validation is based on splitting dataset on _k_ disjoint subsets and using _k-1_ of them as train subset and the remaining subset for test (with all possible combinations). The goal of this task is to implement K-fold cross validation based on an ability to filter dataset added recently in IGNITE-8666. > K-fold cross validation of models > - > > Key: IGNITE-8668 > URL: https://issues.apache.org/jira/browse/IGNITE-8668 > Project: Ignite > Issue Type: New Feature > Components: ml >Reporter: Yury Babak >Assignee: Anton Dmitriev >Priority: Major > Fix For: 2.6 > > > Cross validation is a well knows approach that allows to avoid overfitting > and therefore improve model quality. K-fold cross validation is based on > splitting dataset on _k_ disjoint subsets and using _k-1_ of them as train > subset and the remaining subset for test (with all possible combinations). > The goal of this task is to implement K-fold cross validation based on an > ability to filter dataset added recently in IGNITE-8666. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
