{"action":"created","issue":{"url":"https://api.github.com/repos/mfaruqui/sparse-coding/issues/3","repository_url":"https://api.github.com/repos/mfaruqui/sparse-coding","labels_url":"https://api.github.com/repos/mfaruqui/sparse-coding/issues/3/labels{/name}","comments_url":"https://api.github.com/repos/mfaruqui/sparse-coding/issues/3/comments","events_url":"https://api.github.com/repos/mfaruqui/sparse-coding/issues/3/events","html_url":"https://github.com/mfaruqui/sparse-coding/issues/3","id":192045935,"number":3,"title":"Less sparse when applied to new dataset","user":{"login":"bkj","id":6086781,"avatar_url":"https://avatars.githubusercontent.com/u/6086781?v=3","gravatar_id":"","url":"https://api.github.com/users/bkj","html_url":"https://github.com/bkj","followers_url":"https://api.github.com/users/bkj/followers","following_url":"https://api.github.com/users/bkj/following{/other_user}","gists_url":"https://api.github.com/users/bkj/gists{/gist_id}","starred_url":"https://api.github.com/users/bkj/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/bkj/subscriptions","organizations_url":"https://api.github.com/users/bkj/orgs","repos_url":"https://api.github.com/users/bkj/repos","events_url":"https://api.github.com/users/bkj/events{/privacy}","received_events_url":"https://api.github.com/users/bkj/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":1,"created_at":"2016-11-28T16:08:25Z","updated_at":"2016-11-29T02:04:33Z","closed_at":"2016-11-29T02:04:33Z","body":"I tried applying these algorithms to my own dataset, which consists of ~5K word embeddings (though they're constructed using a less standard method).  Using the same parameters, the results are far less sparse than when using the `glove` embeddings as described in the paper (50% compared to 90%).\r\n\r\nAny ideas why this would be?  Perhaps the number of vectors has some effect (5K vs 400K)?  Some parameter needs tuning?"},"comment":{"url":"https://api.github.com/repos/mfaruqui/sparse-coding/issues/comments/263454968","html_url":"https://github.com/mfaruqui/sparse-coding/issues/3#issuecomment-263454968","issue_url":"https://api.github.com/repos/mfaruqui/sparse-coding/issues/3","id":263454968,"user":{"login":"mfaruqui","id":2390196,"avatar_url":"https://avatars.githubusercontent.com/u/2390196?v=3","gravatar_id":"","url":"https://api.github.com/users/mfaruqui","html_url":"https://github.com/mfaruqui","followers_url":"https://api.github.com/users/mfaruqui/followers","following_url":"https://api.github.com/users/mfaruqui/following{/other_user}","gists_url":"https://api.github.com/users/mfaruqui/gists{/gist_id}","starred_url":"https://api.github.com/users/mfaruqui/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/mfaruqui/subscriptions","organizations_url":"https://api.github.com/users/mfaruqui/orgs","repos_url":"https://api.github.com/users/mfaruqui/repos","events_url":"https://api.github.com/users/mfaruqui/events{/privacy}","received_events_url":"https://api.github.com/users/mfaruqui/received_events","type":"User","site_admin":false},"created_at":"2016-11-29T02:04:33Z","updated_at":"2016-11-29T02:04:33Z","body":"You can try increasing the parameter value of the L1 regularisation. The more you will increase it, the sparser your vectors will become."}}
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