{"action":"created","issue":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/3942","repository_url":"https://api.github.com/repos/scikit-learn/scikit-learn","labels_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/3942/labels{/name}","comments_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/3942/comments","events_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/3942/events","html_url":"https://github.com/scikit-learn/scikit-learn/pull/3942","id":51213875,"number":3942,"title":"[MRG+1] Kernel Ridge Regression","user":{"login":"jmetzen","id":1116263,"avatar_url":"https://avatars.githubusercontent.com/u/1116263?v=3","gravatar_id":"","url":"https://api.github.com/users/jmetzen","html_url":"https://github.com/jmetzen","followers_url":"https://api.github.com/users/jmetzen/followers","following_url":"https://api.github.com/users/jmetzen/following{/other_user}","gists_url":"https://api.github.com/users/jmetzen/gists{/gist_id}","starred_url":"https://api.github.com/users/jmetzen/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/jmetzen/subscriptions","organizations_url":"https://api.github.com/users/jmetzen/orgs","repos_url":"https://api.github.com/users/jmetzen/repos","events_url":"https://api.github.com/users/jmetzen/events{/privacy}","received_events_url":"https://api.github.com/users/jmetzen/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"milestone":null,"comments":21,"created_at":"2014-12-07T10:26:47Z","updated_at":"2016-02-04T01:50:48Z","closed_at":"2015-01-18T05:50:09Z","pull_request":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/3942","html_url":"https://github.com/scikit-learn/scikit-learn/pull/3942","diff_url":"https://github.com/scikit-learn/scikit-learn/pull/3942.diff","patch_url":"https://github.com/scikit-learn/scikit-learn/pull/3942.patch"},"body":"Adds an implementation of Kernel Ridge Regression (KRR)\r\n\r\nBasic implementation of KRR based on @mblondel's code in lightning. In addition to the lighning code, documentation and an example comparing KRR and SVR is added. The example illustrates the models learned by KRR and SVR:\r\n\r\n![plot_kernel_ridge_regression_001](https://cloud.githubusercontent.com/assets/1116263/5330658/9793f8f6-7e03-11e4-93a9-7da2f0634037.png)\r\n\r\nFurthermore, it compares the time required for fitting the model and predicting with the model for different sizes of the training set:\r\n\r\n![plot_kernel_ridge_regression_002](https://cloud.githubusercontent.com/assets/1116263/5330660/a1b7a4cc-7e03-11e4-8628-3d6cccad921a.png)\r\n"},"comment":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/comments/179570126","html_url":"https://github.com/scikit-learn/scikit-learn/pull/3942#issuecomment-179570126","issue_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/3942","id":179570126,"user":{"login":"mblondel","id":233706,"avatar_url":"https://avatars.githubusercontent.com/u/233706?v=3","gravatar_id":"","url":"https://api.github.com/users/mblondel","html_url":"https://github.com/mblondel","followers_url":"https://api.github.com/users/mblondel/followers","following_url":"https://api.github.com/users/mblondel/following{/other_user}","gists_url":"https://api.github.com/users/mblondel/gists{/gist_id}","starred_url":"https://api.github.com/users/mblondel/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/mblondel/subscriptions","organizations_url":"https://api.github.com/users/mblondel/orgs","repos_url":"https://api.github.com/users/mblondel/repos","events_url":"https://api.github.com/users/mblondel/events{/privacy}","received_events_url":"https://api.github.com/users/mblondel/received_events","type":"User","site_admin":false},"created_at":"2016-02-04T01:50:48Z","updated_at":"2016-02-04T01:50:48Z","body":"@dougalsutherland The functionality is essentially there since RidgeCV supports the n_features > n_samples case. It's just a matter of extracting the code and exposing it in an estimator class. PR welcome :)"}}