{"action":"opened","issue":{"url":"https://api.github.com/repos/facebookresearch/faiss/issues/678","repository_url":"https://api.github.com/repos/facebookresearch/faiss","labels_url":"https://api.github.com/repos/facebookresearch/faiss/issues/678/labels{/name}","comments_url":"https://api.github.com/repos/facebookresearch/faiss/issues/678/comments","events_url":"https://api.github.com/repos/facebookresearch/faiss/issues/678/events","html_url":"https://github.com/facebookresearch/faiss/issues/678","id":394554674,"node_id":"MDU6SXNzdWUzOTQ1NTQ2NzQ=","number":678,"title":"How to output the results of faiss::Clustering kMeans","user":{"login":"kakadadudu","id":22951851,"node_id":"MDQ6VXNlcjIyOTUxODUx","avatar_url":"https://avatars1.githubusercontent.com/u/22951851?v=4","gravatar_id":"","url":"https://api.github.com/users/kakadadudu","html_url":"https://github.com/kakadadudu","followers_url":"https://api.github.com/users/kakadadudu/followers","following_url":"https://api.github.com/users/kakadadudu/following{/other_user}","gists_url":"https://api.github.com/users/kakadadudu/gists{/gist_id}","starred_url":"https://api.github.com/users/kakadadudu/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/kakadadudu/subscriptions","organizations_url":"https://api.github.com/users/kakadadudu/orgs","repos_url":"https://api.github.com/users/kakadadudu/repos","events_url":"https://api.github.com/users/kakadadudu/events{/privacy}","received_events_url":"https://api.github.com/users/kakadadudu/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-12-28T05:59:21Z","updated_at":"2018-12-28T05:59:21Z","closed_at":null,"author_association":"NONE","body":"For example, I have 1000 documents. After extracting a 256-dimensional feature from none of them, I use K function to cluster them into 10 automatically. For this；\r\n\r\n`faiss::ClusteringParameters cp;\r\ncp.niter = numberOfEMIterations;\r\ncp.verbose = true;\r\nfaiss::Clustering kMeans(dim, numberOfClusters, cp);\r\nkMeans.train(numVecsToCluster, fDataset, index); `\r\n\r\nHow to output the clustered results according to different categories?\r\n"}}
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