{"action":"created","comment":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/comments/76000254","id":76000254,"diff_hunk":"@@ -290,6 +290,40 @@ both testing and training. Notice that the folds do not have exactly the same\n size due to the imbalance in the data.\n \n \n+.. _homogeneous_time_series_cv:\n+\n+HomogeneousTimeSeriesCV\n+-----------------------\n+\n+:class:`HomogeneousTimeSeriesCV` is a variation of *k-fold* which \n+returns first :math:`k` folds as train set and the :math:`(k+1)` th \n+fold as test set. Note that unlike standard cross-validation methods, \n+successive training sets are supersets of those that come before them.\n+Also, its foldsizes is not in accordance with :class:`KFold`,\n+it add all surplus data to the first training partition, which\n+is always used to train the model.\n+\n+This class can be used to cross-validate homogeneous time series data,\n+i.e., samples are observed at fixed time intervals.","path":"doc/modules/cross_validation.rst","position":null,"original_position":18,"commit_id":"dbf1f159d15ec3d795ce865bd20babef34ddd53b","original_commit_id":"a4593386e4225889b9d93f1bfbe9adba495af7a1","user":{"login":"yenchenlin","id":7057863,"avatar_url":"https://avatars.githubusercontent.com/u/7057863?v=3","gravatar_id":"","url":"https://api.github.com/users/yenchenlin","html_url":"https://github.com/yenchenlin","followers_url":"https://api.github.com/users/yenchenlin/followers","following_url":"https://api.github.com/users/yenchenlin/following{/other_user}","gists_url":"https://api.github.com/users/yenchenlin/gists{/gist_id}","starred_url":"https://api.github.com/users/yenchenlin/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/yenchenlin/subscriptions","organizations_url":"https://api.github.com/users/yenchenlin/orgs","repos_url":"https://api.github.com/users/yenchenlin/repos","events_url":"https://api.github.com/users/yenchenlin/events{/privacy}","received_events_url":"https://api.github.com/users/yenchenlin/received_events","type":"User","site_admin":false},"body":"thanks! \r\n\r\nI've addressed the comments from you and other reviewers, have a look once you get time!","created_at":"2016-08-24T06:21:14Z","updated_at":"2016-08-24T06:21:14Z","html_url":"https://github.com/scikit-learn/scikit-learn/pull/6586#discussion_r76000254","pull_request_url":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/6586","_links":{"self":{"href":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/comments/76000254"},"html":{"href":"https://github.com/scikit-learn/scikit-learn/pull/6586#discussion_r76000254"},"pull_request":{"href":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/6586"}}},"pull_request":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/6586","id":63992637,"html_url":"https://github.com/scikit-learn/scikit-learn/pull/6586","diff_url":"https://github.com/scikit-learn/scikit-learn/pull/6586.diff","patch_url":"https://github.com/scikit-learn/scikit-learn/pull/6586.patch","issue_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/6586","number":6586,"state":"open","locked":false,"title":"[MRG+2?] Add homogeneous time series cross validation","user":{"login":"yenchenlin","id":7057863,"avatar_url":"https://avatars.githubusercontent.com/u/7057863?v=3","gravatar_id":"","url":"https://api.github.com/users/yenchenlin","html_url":"https://github.com/yenchenlin","followers_url":"https://api.github.com/users/yenchenlin/followers","following_url":"https://api.github.com/users/yenchenlin/following{/other_user}","gists_url":"https://api.github.com/users/yenchenlin/gists{/gist_id}","starred_url":"https://api.github.com/users/yenchenlin/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/yenchenlin/subscriptions","organizations_url":"https://api.github.com/users/yenchenlin/orgs","repos_url":"https://api.github.com/users/yenchenlin/repos","events_url":"https://api.github.com/users/yenchenlin/events{/privacy}","received_events_url":"https://api.github.com/users/yenchenlin/received_events","type":"User","site_admin":false},"body":"This PR is a separated PR from #6351 that tries to solve #6322 ,\r\nand it implements homogeneous time series cross validation and add the corresponding test. \r\n\r\nHowever, there's a discussion on `n_folds`'s meaning [here](https://github.com/scikit-learn/scikit-learn/pull/6351#discussion_r55256952), may reviewers please give me some suggestion?\r\n\r\nping @MechCoder @rvraghav93 @amueller @jnothman :pray: 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