{"action":"created","issue":{"url":"https://api.github.com/repos/rhiever/tpot/issues/125","repository_url":"https://api.github.com/repos/rhiever/tpot","labels_url":"https://api.github.com/repos/rhiever/tpot/issues/125/labels{/name}","comments_url":"https://api.github.com/repos/rhiever/tpot/issues/125/comments","events_url":"https://api.github.com/repos/rhiever/tpot/issues/125/events","html_url":"https://github.com/rhiever/tpot/issues/125","id":147570626,"number":125,"title":"Examples: provide an example based a real dataset","user":{"login":"loretoparisi","id":163333,"avatar_url":"https://avatars.githubusercontent.com/u/163333?v=3","gravatar_id":"","url":"https://api.github.com/users/loretoparisi","html_url":"https://github.com/loretoparisi","followers_url":"https://api.github.com/users/loretoparisi/followers","following_url":"https://api.github.com/users/loretoparisi/following{/other_user}","gists_url":"https://api.github.com/users/loretoparisi/gists{/gist_id}","starred_url":"https://api.github.com/users/loretoparisi/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/loretoparisi/subscriptions","organizations_url":"https://api.github.com/users/loretoparisi/orgs","repos_url":"https://api.github.com/users/loretoparisi/repos","events_url":"https://api.github.com/users/loretoparisi/events{/privacy}","received_events_url":"https://api.github.com/users/loretoparisi/received_events","type":"User","site_admin":false},"labels":[{"url":"https://api.github.com/repos/rhiever/tpot/labels/question","name":"question","color":"cc317c"}],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":6,"created_at":"2016-04-11T22:12:47Z","updated_at":"2016-04-11T23:22:57Z","closed_at":null,"body":"I'm trying to figure out a real-world example with `tpot` to learn how it works, step by step.\r\n\r\nSo, I will take [this](http://stackoverflow.com/questions/36535239/natural-language-processing-of-topics/36538038#36538038) dataset as example, that looks like\r\n\r\n```json\r\n{\r\n    \"laughter-good-conversation-friendships\": {\r\n        \"category\": \"socializing\",\r\n        \"category_id\": 31,\r\n        \"score\": 2.5,\r\n        \"topic_id\": 27166\r\n    },\r\n    \"live-theatre\": {\r\n        \"category\": \"socializing\",\r\n        \"category_id\": 31,\r\n        \"score\": 2.5,\r\n        \"topic_id\": 23274\r\n    },\r\n    \"nightlife\": {\r\n        \"category\": \"socializing\",\r\n        \"category_id\": 31,\r\n        \"score\": 2.5,\r\n        \"topic_id\": 4392\r\n    },\r\n    \"wine-tasting\": {\r\n        \"category\": \"socializing\",\r\n        \"category_id\": 31,\r\n        \"score\": 2.5,\r\n        \"topic_id\": 15139\r\n    },\r\n    \"women\": {\r\n        \"category\": \"socializing\",\r\n        \"category_id\": 31,\r\n        \"score\": 2.5,\r\n        \"topic_id\": 10232\r\n    },\r\n    \"business-entrepreneur-networking\": {\r\n        \"category\": \"career-business\",\r\n        \"category_id\": 2,\r\n        \"score\": 0,\r\n        \"topic_id\": 20060\r\n    },\r\n    \"business-referral-networking\": {\r\n        \"category\": \"career-business\",\r\n        \"category_id\": 2,\r\n        \"score\": 0,\r\n        \"topic_id\": 15405\r\n    },\r\n    \"christian\": {\r\n        \"category\": \"career-business\",\r\n        \"category_id\": 2,\r\n        \"score\": 0,\r\n        \"topic_id\": 17963\r\n    },\r\n    \"financial-chaos-to-financial-freedom\": {\r\n        \"category\": \"career-business\",\r\n        \"category_id\": 2,\r\n        \"score\": 0,\r\n        \"topic_id\": 79053\r\n    },\r\n    \"insprofs\": {\r\n        \"category\": \"career-business\",\r\n        \"category_id\": 2,\r\n        \"score\": 0,\r\n        \"topic_id\": 10042\r\n    },\r\n    \"professional-networking\": {\r\n        \"category\": \"career-business\",\r\n        \"category_id\": 2,\r\n        \"score\": 0,\r\n        \"topic_id\": 15720\r\n    },\r\n    \"real-estate-investors\": {\r\n        \"category\": \"career-business\",\r\n        \"category_id\": 2,\r\n        \"score\": 0,\r\n        \"topic_id\": 16165\r\n    },\r\n    \"retirement\": {\r\n        \"category\": \"career-business\",\r\n        \"category_id\": 2,\r\n        \"score\": 0,\r\n        \"topic_id\": 6364\r\n    },\r\n    \"socialnetwork\": {\r\n        \"category\": \"career-business\",\r\n        \"category_id\": 2,\r\n        \"score\": 0,\r\n        \"topic_id\": 4422\r\n    }\r\n}\r\n```\r\n\r\neach item in this json is a topic like `socialnetwork`  that belongs to a category like `career-business`. More topics may belong to the same category, like `wine-tasting` and `nightlife` belongs to `socializing`, son in a 1 to N relationship.\r\nNow, the are some topics that may affer to the same topic like here:\r\n\r\n```json\r\n\"dragons\": {\r\n        \"category\": \"lifestyle\",\r\n        \"category_id\": 17,\r\n        \"score\": 0.279108277990115,\r\n        \"topic_id\": 2137\r\n    },\r\n    \"furry-fandom\": {\r\n        \"category\": \"lifestyle\",\r\n        \"category_id\": 17,\r\n        \"score\": 0.279108277990115,\r\n        \"topic_id\": 48595\r\n    },\r\n    \"legendarycreatures\": {\r\n        \"category\": \"lifestyle\",\r\n        \"category_id\": 17,\r\n        \"score\": 0.279108277990115,\r\n        \"topic_id\": 10523\r\n    }\r\n```\r\n\r\nTopics like `dragons` and `legendarycreatures` could be considered part of a new topic like `fantasy`.\r\nSo, assumed that `tpot` can analyze dataset automatically, how to describe this dataset in order that our `objective function` is to collect / aggregate topics in new topics, so new categories that are not defined in this dataset?"},"comment":{"url":"https://api.github.com/repos/rhiever/tpot/issues/comments/208613487","html_url":"https://github.com/rhiever/tpot/issues/125#issuecomment-208613487","issue_url":"https://api.github.com/repos/rhiever/tpot/issues/125","id":208613487,"user":{"login":"loretoparisi","id":163333,"avatar_url":"https://avatars.githubusercontent.com/u/163333?v=3","gravatar_id":"","url":"https://api.github.com/users/loretoparisi","html_url":"https://github.com/loretoparisi","followers_url":"https://api.github.com/users/loretoparisi/followers","following_url":"https://api.github.com/users/loretoparisi/following{/other_user}","gists_url":"https://api.github.com/users/loretoparisi/gists{/gist_id}","starred_url":"https://api.github.com/users/loretoparisi/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/loretoparisi/subscriptions","organizations_url":"https://api.github.com/users/loretoparisi/orgs","repos_url":"https://api.github.com/users/loretoparisi/repos","events_url":"https://api.github.com/users/loretoparisi/events{/privacy}","received_events_url":"https://api.github.com/users/loretoparisi/received_events","type":"User","site_admin":false},"created_at":"2016-04-11T23:22:57Z","updated_at":"2016-04-11T23:22:57Z","body":"@rhiever ok, which is the input data format, let's say a typical row I would have from the `word2vec` vector for a label is the array of floating point numbers, do this work?"}}