{"action":"created","issue":{"url":"https://api.github.com/repos/shogun-toolbox/shogun/issues/3054","repository_url":"https://api.github.com/repos/shogun-toolbox/shogun","labels_url":"https://api.github.com/repos/shogun-toolbox/shogun/issues/3054/labels{/name}","comments_url":"https://api.github.com/repos/shogun-toolbox/shogun/issues/3054/comments","events_url":"https://api.github.com/repos/shogun-toolbox/shogun/issues/3054/events","html_url":"https://github.com/shogun-toolbox/shogun/issues/3054","id":139328674,"number":3054,"title":"benchmark GPs against sklearn, gpy, gpflow, and gpml","user":{"login":"yorkerlin","id":6913996,"avatar_url":"https://avatars.githubusercontent.com/u/6913996?v=3","gravatar_id":"","url":"https://api.github.com/users/yorkerlin","html_url":"https://github.com/yorkerlin","followers_url":"https://api.github.com/users/yorkerlin/followers","following_url":"https://api.github.com/users/yorkerlin/following{/other_user}","gists_url":"https://api.github.com/users/yorkerlin/gists{/gist_id}","starred_url":"https://api.github.com/users/yorkerlin/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/yorkerlin/subscriptions","organizations_url":"https://api.github.com/users/yorkerlin/orgs","repos_url":"https://api.github.com/users/yorkerlin/repos","events_url":"https://api.github.com/users/yorkerlin/events{/privacy}","received_events_url":"https://api.github.com/users/yorkerlin/received_events","type":"User","site_admin":false},"labels":[{"url":"https://api.github.com/repos/shogun-toolbox/shogun/labels/entrance","name":"entrance","color":"e102d8"}],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":15,"created_at":"2016-03-08T16:45:54Z","updated_at":"2016-03-23T16:47:10Z","closed_at":null,"body":"This entrance task is about doing benchmarks against [sklearn v0.18](http://scikit-learn.org/dev/modules/gaussian_process.html), [gpy](https://github.com/SheffieldML/GPy), [gpflow](https://github.com/GPflow/GPflow), and [gpml](http://www.gaussianprocess.org/gpml/code/matlab/doc/) in terms of speed, memory usage, and accuracy.\r\n\r\nSome tasks:\r\n* Gaussian process (GP) regression \r\n* GP binary classification using Logistic likelihood\r\n\r\nNote that for GP binary classification, there are many implemented inference algorithms (eg, EP, Laplace, and KL) in Shogun. \r\n\r\nHint:\r\n* For GP binary classification,sklearn (v0.18dev0) only has the Laplace implementation.  \r\n* There is no sparse GP implementation in sklearn (v0.18dev0) \r\n"},"comment":{"url":"https://api.github.com/repos/shogun-toolbox/shogun/issues/comments/200434905","html_url":"https://github.com/shogun-toolbox/shogun/issues/3054#issuecomment-200434905","issue_url":"https://api.github.com/repos/shogun-toolbox/shogun/issues/3054","id":200434905,"user":{"login":"karlnapf","id":699071,"avatar_url":"https://avatars.githubusercontent.com/u/699071?v=3","gravatar_id":"","url":"https://api.github.com/users/karlnapf","html_url":"https://github.com/karlnapf","followers_url":"https://api.github.com/users/karlnapf/followers","following_url":"https://api.github.com/users/karlnapf/following{/other_user}","gists_url":"https://api.github.com/users/karlnapf/gists{/gist_id}","starred_url":"https://api.github.com/users/karlnapf/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/karlnapf/subscriptions","organizations_url":"https://api.github.com/users/karlnapf/orgs","repos_url":"https://api.github.com/users/karlnapf/repos","events_url":"https://api.github.com/users/karlnapf/events{/privacy}","received_events_url":"https://api.github.com/users/karlnapf/received_events","type":"User","site_admin":false},"created_at":"2016-03-23T16:47:10Z","updated_at":"2016-03-23T16:47:10Z","body":"We should compare a benchmark where we also learn the hyper-parameters using ML2."}}