{"action":"created","issue":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/5275","labels_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/5275/labels{/name}","comments_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/5275/comments","events_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/5275/events","html_url":"https://github.com/scikit-learn/scikit-learn/issues/5275","id":106653806,"number":5275,"title":"DBSCAN memory consumption","user":{"login":"cstich","id":9212959,"avatar_url":"https://avatars.githubusercontent.com/u/9212959?v=3","gravatar_id":"","url":"https://api.github.com/users/cstich","html_url":"https://github.com/cstich","followers_url":"https://api.github.com/users/cstich/followers","following_url":"https://api.github.com/users/cstich/following{/other_user}","gists_url":"https://api.github.com/users/cstich/gists{/gist_id}","starred_url":"https://api.github.com/users/cstich/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/cstich/subscriptions","organizations_url":"https://api.github.com/users/cstich/orgs","repos_url":"https://api.github.com/users/cstich/repos","events_url":"https://api.github.com/users/cstich/events{/privacy}","received_events_url":"https://api.github.com/users/cstich/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":14,"created_at":"2015-09-15T21:39:59Z","updated_at":"2015-10-12T14:12:53Z","closed_at":null,"body":"Hi,\r\n\r\nI am using DBSCAN to cluster some points of mine and I run into some possibly memory related issues. If I try to cluster something in the ballpark of 50k two-dimensional points with the haversine metric, I am running out of memory on a machine with 16GB, and I am not sure that this is supposed to happen. I mean, 50k isn't that many points, or am I wrong?\r\n\r\nFor the last two times I tried I also got this line repeated over and over again:\r\n\r\n    File \"sklearn/cluster/_dbscan_inner.pyx\", line 14, in sklearn.cluster._dbscan_inner.push (sklearn/cluster/_dbscan_inner.cpp:1243) \r\n\r\nFollowed by\r\n\r\n    MemoryError: std::bad_alloc \r\n\r\nI call DBSCAN like this:\r\n\r\n    eps = 50 / (1000*6378.137)\r\n    db = DBSCAN(eps=eps, min_samples=3,  algorithm='ball_tree', metric='haversine').fit(x)\r\n\r\nI am on Python 2.7 and scikit-learn 0.16."},"comment":{"url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/comments/147409920","html_url":"https://github.com/scikit-learn/scikit-learn/issues/5275#issuecomment-147409920","issue_url":"https://api.github.com/repos/scikit-learn/scikit-learn/issues/5275","id":147409920,"user":{"login":"cstich","id":9212959,"avatar_url":"https://avatars.githubusercontent.com/u/9212959?v=3","gravatar_id":"","url":"https://api.github.com/users/cstich","html_url":"https://github.com/cstich","followers_url":"https://api.github.com/users/cstich/followers","following_url":"https://api.github.com/users/cstich/following{/other_user}","gists_url":"https://api.github.com/users/cstich/gists{/gist_id}","starred_url":"https://api.github.com/users/cstich/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/cstich/subscriptions","organizations_url":"https://api.github.com/users/cstich/orgs","repos_url":"https://api.github.com/users/cstich/repos","events_url":"https://api.github.com/users/cstich/events{/privacy}","received_events_url":"https://api.github.com/users/cstich/received_events","type":"User","site_admin":false},"created_at":"2015-10-12T14:12:53Z","updated_at":"2015-10-12T14:12:53Z","body":"Thanks for the feedback and that makes sense. I am still slightly confused though, I can cluster my points just fine in 0.15 but run out of memory in 0.16"}}