{"action":"created","comment":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/comments/23092413","id":23092413,"diff_hunk":"@@ -260,29 +260,32 @@ class GraphLasso(EmpiricalCovariance):\n \n     Parameters\n     ----------\n-    alpha : positive float, optional\n+    alpha : positive float, default 0.01\n         The regularization parameter: the higher alpha, the more\n         regularization, the sparser the inverse covariance.\n \n-    cov_init : 2D array (n_features, n_features), optional\n-        The initial guess for the covariance.\n-\n-    mode : {'cd', 'lars'}\n+    mode : {'cd', 'lars'}, default 'cd'\n         The Lasso solver to use: coordinate descent or LARS. Use LARS for\n         very sparse underlying graphs, where p > n. Elsewhere prefer cd\n         which is more numerically stable.\n \n-    tol : positive float, optional\n+    tol : positive float, default 1e-4\n         The tolerance to declare convergence: if the dual gap goes below\n         this value, iterations are stopped.\n \n-    max_iter : integer, optional\n+    max_iter : integer, default 100\n         The maximum number of iterations.\n \n-    verbose : boolean, optional\n+    verbose : boolean, default False\n         If verbose is True, the objective function and dual gap are\n         plotted at each iteration.\n \n+    assume_centered : boolean, default False\n+        If True, data are not centered before computation.\n+        Useful when working with data whose mean is almost, but not exactly\n+        zero.\n+        If False, data are centered before computation.","path":"sklearn/covariance/graph_lasso_.py","position":36,"original_position":36,"commit_id":"3f6058a87770f0924daab7fa98f93e50b4e59695","original_commit_id":"3f6058a87770f0924daab7fa98f93e50b4e59695","user":{"login":"ogrisel","id":89061,"avatar_url":"https://avatars.githubusercontent.com/u/89061?v=3","gravatar_id":"","url":"https://api.github.com/users/ogrisel","html_url":"https://github.com/ogrisel","followers_url":"https://api.github.com/users/ogrisel/followers","following_url":"https://api.github.com/users/ogrisel/following{/other_user}","gists_url":"https://api.github.com/users/ogrisel/gists{/gist_id}","starred_url":"https://api.github.com/users/ogrisel/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/ogrisel/subscriptions","organizations_url":"https://api.github.com/users/ogrisel/orgs","repos_url":"https://api.github.com/users/ogrisel/repos","events_url":"https://api.github.com/users/ogrisel/events{/privacy}","received_events_url":"https://api.github.com/users/ogrisel/received_events","type":"User","site_admin":false},"body":"+1","created_at":"2015-01-16T16:50:47Z","updated_at":"2015-01-16T16:50:47Z","html_url":"https://github.com/scikit-learn/scikit-learn/pull/4023#discussion_r23092413","pull_request_url":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/4023","_links":{"self":{"href":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/comments/23092413"},"html":{"href":"https://github.com/scikit-learn/scikit-learn/pull/4023#discussion_r23092413"},"pull_request":{"href":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/4023"}}},"pull_request":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/pulls/4023","id":26631232,"html_url":"https://github.com/scikit-learn/scikit-learn/pull/4023","diff_url":"https://github.com/scikit-learn/scikit-learn/pull/4023.diff","patch_url":"https://github.com/scikit-learn/scikit-learn/pull/4023.patch","issue_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/4023","number":4023,"state":"open","locked":false,"title":"[MRG+1] Fix doc signature mismatch","user":{"login":"ragv","id":9487348,"avatar_url":"https://avatars.githubusercontent.com/u/9487348?v=3","gravatar_id":"","url":"https://api.github.com/users/ragv","html_url":"https://github.com/ragv","followers_url":"https://api.github.com/users/ragv/followers","following_url":"https://api.github.com/users/ragv/following{/other_user}","gists_url":"https://api.github.com/users/ragv/gists{/gist_id}","starred_url":"https://api.github.com/users/ragv/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/ragv/subscriptions","organizations_url":"https://api.github.com/users/ragv/orgs","repos_url":"https://api.github.com/users/ragv/repos","events_url":"https://api.github.com/users/ragv/events{/privacy}","received_events_url":"https://api.github.com/users/ragv/received_events","type":"User","site_admin":false},"body":"Fixes #2062 \r\n\r\n- [x] Make all docstrings match with signatures. ( 120 / 120 )\r\n- [x] Rename invalid sections to valid numpydoc defined sections\r\n  * `Caveats` --> `Notes`\r\n  * `Reference` --> `References`\r\n  * `Example` --> `Examples` etc...\r\n- [x] Cross check and scavenge #2084 for reviews / improvised docstrings etc...\r\n- [x] Replace `FIXME` ( in docstring ) with relevant text...\r\n\r\n~~Consistently remove `optional` across all docstrings and specify the `default` value directly...~~\r\n\r\n@jnothman @amueller @NelleV Kindly take a look... 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