{"action":"opened","issue":{"url":"https://api.github.com/repos/ai-se/Pits_lda/issues/34","repository_url":"https://api.github.com/repos/ai-se/Pits_lda","labels_url":"https://api.github.com/repos/ai-se/Pits_lda/issues/34/labels{/name}","comments_url":"https://api.github.com/repos/ai-se/Pits_lda/issues/34/comments","events_url":"https://api.github.com/repos/ai-se/Pits_lda/issues/34/events","html_url":"https://github.com/ai-se/Pits_lda/issues/34","id":182314632,"number":34,"title":"Credibility Of LDA","user":{"login":"amritbhanu","id":3458568,"avatar_url":"https://avatars.githubusercontent.com/u/3458568?v=3","gravatar_id":"","url":"https://api.github.com/users/amritbhanu","html_url":"https://github.com/amritbhanu","followers_url":"https://api.github.com/users/amritbhanu/followers","following_url":"https://api.github.com/users/amritbhanu/following{/other_user}","gists_url":"https://api.github.com/users/amritbhanu/gists{/gist_id}","starred_url":"https://api.github.com/users/amritbhanu/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/amritbhanu/subscriptions","organizations_url":"https://api.github.com/users/amritbhanu/orgs","repos_url":"https://api.github.com/users/amritbhanu/repos","events_url":"https://api.github.com/users/amritbhanu/events{/privacy}","received_events_url":"https://api.github.com/users/amritbhanu/received_events","type":"User","site_admin":false},"labels":[{"url":"https://api.github.com/repos/ai-se/Pits_lda/labels/Result","name":"Result","color":"d4c5f9"}],"state":"open","locked":false,"assignee":{"login":"timm","id":29195,"avatar_url":"https://avatars.githubusercontent.com/u/29195?v=3","gravatar_id":"","url":"https://api.github.com/users/timm","html_url":"https://github.com/timm","followers_url":"https://api.github.com/users/timm/followers","following_url":"https://api.github.com/users/timm/following{/other_user}","gists_url":"https://api.github.com/users/timm/gists{/gist_id}","starred_url":"https://api.github.com/users/timm/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/timm/subscriptions","organizations_url":"https://api.github.com/users/timm/orgs","repos_url":"https://api.github.com/users/timm/repos","events_url":"https://api.github.com/users/timm/events{/privacy}","received_events_url":"https://api.github.com/users/timm/received_events","type":"User","site_admin":false},"assignees":[{"login":"timm","id":29195,"avatar_url":"https://avatars.githubusercontent.com/u/29195?v=3","gravatar_id":"","url":"https://api.github.com/users/timm","html_url":"https://github.com/timm","followers_url":"https://api.github.com/users/timm/followers","following_url":"https://api.github.com/users/timm/following{/other_user}","gists_url":"https://api.github.com/users/timm/gists{/gist_id}","starred_url":"https://api.github.com/users/timm/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/timm/subscriptions","organizations_url":"https://api.github.com/users/timm/orgs","repos_url":"https://api.github.com/users/timm/repos","events_url":"https://api.github.com/users/timm/events{/privacy}","received_events_url":"https://api.github.com/users/timm/received_events","type":"User","site_admin":false}],"milestone":null,"comments":0,"created_at":"2016-10-11T16:41:47Z","updated_at":"2016-10-11T16:41:47Z","closed_at":null,"body":"## IDEA:\r\n```\r\nACTUAL\r\n          T1        T2         T3      .. .. . . .\r\nDoc1\r\nDoc2\r\nDoc3\r\n\r\nPREDICTED - Selected from Dominant topic from doc topic distribution.\r\n          W1        W2         W3      .. .. . . .\r\nDoc1\r\nDoc2\r\nDoc3\r\n\r\n**According to literature, If a document is asked to belong to one of the dominant topic (hard assignment), the top words from the dominant topic should be in the actual document. If not:\r\n - then the probability of dominant topic is very less and there might be other topic which can be made dominant.\r\n- or the top words are wrongly selected. The weights of words could be better to find the same dominant topic.**\r\n```\r\n\r\n## Experiment:\r\n- Once top n words are selected from each topic, now those topics are represented with those n words.\r\n- A dominant topic is selected to represent a document, we call that as actual.\r\n- we will check for each topic which are now represented with n words. We will find most 'm 'words out of those 'n' in a document. Whichever topic will have the most 'm' words, according to this, now that document is represented with this topic.\r\n\r\n```\r\nWe have now x no of documents. For eg x=4, k(no of topics)=3\r\nActual=[1,1,2]\r\nPredicted=[1,0,2]\r\nThe score is = 2/3=0.67\r\n```\r\n\r\n## Results:\r\n- Higher the better\r\n![file](https://github.com/ai-se/Pits_lda/raw/master/src/10-01/stability.png)\r\n\r\n## Conclusion:\r\n- tuned with top 7 words is performing much better than untuned (default, k=10) top 7 words.\r\n- tuned with top 7 words is performing better or same than untuned (default, k=10) top 10 words.\r\n- With tuning we have better top 7 words defining that topic."}}
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