{
  "id": 201169,
  "title": "Best Single Model",
  "url": "/competitions/riiid-test-answer-prediction/discussion/201169",
  "author_name": "",
  "post_date": "2020-12-03T13:33:04.518081Z",
  "votes": 9,
  "comment_count": 7,
  "views": 0,
  "content": "<p>Hi all, </p>\n<p>Have not seen the topic with best single model discussion so creating one here. </p>\n<p>Starting with me, I have just started working in this competition.<br>\nModel = LGBM<br>\nLB = 0.760<br>\nCV = 0.755<br>\nSingle Fold</p>\n<p>So what is your best single model score? </p>",
  "messages": [
    {
      "id": "1100930",
      "postDate": "12/03/2020 13:33:04",
      "content": "<p>Hi all, </p>\n<p>Have not seen the topic with best single model discussion so creating one here. </p>\n<p>Starting with me, I have just started working in this competition.<br>\nModel = LGBM<br>\nLB = 0.760<br>\nCV = 0.755<br>\nSingle Fold</p>\n<p>So what is your best single model score? </p>",
      "rawMarkdown": "Hi all, \n\nHave not seen the topic with best single model discussion so creating one here. \n\nStarting with me, I have just started working in this competition.\nModel = LGBM\nLB = 0.760\nCV = 0.755\nSingle Fold\n\nSo what is your best single model score?",
      "votes": null
    },
    {
      "id": "1101236",
      "postDate": "12/03/2020 18:27:37",
      "content": "<p>just a question please ? Are you using all the train data ?  </p>",
      "rawMarkdown": "just a question please ? Are you using all the train data ?",
      "votes": null
    },
    {
      "id": "1101450",
      "postDate": "12/03/2020 22:57:37",
      "content": "<p>Using 10M rows to train.</p>\n<p>Single model lgbm, single fold val.</p>\n<p>Val score: 0.765, lb score: 0.765</p>",
      "rawMarkdown": "Using 10M rows to train.\n\nSingle model lgbm, single fold val.\n\nVal score: 0.765, lb score: 0.765",
      "votes": null
    },
    {
      "id": "1101548",
      "postDate": "12/04/2020 02:26:14",
      "content": "<p>Model = XGB<br>\nLB = 0.771<br>\nSingle Fold Validation AUC = 0.7679</p>\n<p>I use all the train data, but I think it does not need to use all.</p>",
      "rawMarkdown": "Model = XGB\nLB = 0.771\nSingle Fold Validation AUC = 0.7679\n\nI use all the train data, but I think it does not need to use all.",
      "votes": null
    },
    {
      "id": "1101552",
      "postDate": "12/04/2020 02:30:16",
      "content": "<p>The best single model score I've seen is LB0.801, awesome!<br>\nthis<a href=\"url\" target=\"_blank\">https://www.kaggle.com/c/riiid-test-answer-prediction/discussion/192919</a></p>",
      "rawMarkdown": "The best single model score I've seen is LB0.801, awesome!\nthis[https://www.kaggle.com/c/riiid-test-answer-prediction/discussion/192919](url)",
      "votes": null
    },
    {
      "id": "1101644",
      "postDate": "12/04/2020 05:15:42",
      "content": "<p>Model = LightGBM<br>\nLB : 0.769<br>\nCV : 0.7686</p>",
      "rawMarkdown": "Model = LightGBM\nLB : 0.769\nCV : 0.7686",
      "votes": null
    },
    {
      "id": "1110036",
      "postDate": "12/12/2020 11:09:15",
      "content": "<p>Model: LightGBM<br>\nLB: 0.700<br>\nCV: 0.798<br>\nI dont know what caused this much gap.</p>",
      "rawMarkdown": "Model: LightGBM\nLB: 0.700\nCV: 0.798\nI dont know what caused this much gap.",
      "votes": null
    },
    {
      "id": "1118327",
      "postDate": "12/19/2020 00:28:27",
      "content": "<p>Model: LGB<br>\nLB: 0.787<br>\nCV: 0.787937, single fold</p>",
      "rawMarkdown": "Model: LGB\nLB: 0.787\nCV: 0.787937, single fold",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 1101236,
      "author_name": "rpygamer",
      "author_url": "",
      "post_date": "12/03/2020 18:27:37",
      "content": "<p>just a question please ? Are you using all the train data ?  </p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 1101450,
      "author_name": "ragnar123",
      "author_url": "",
      "post_date": "12/03/2020 22:57:37",
      "content": "<p>Using 10M rows to train.</p>\n<p>Single model lgbm, single fold val.</p>\n<p>Val score: 0.765, lb score: 0.765</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 1101548,
      "author_name": "takamichitoda",
      "author_url": "",
      "post_date": "12/04/2020 02:26:14",
      "content": "<p>Model = XGB<br>\nLB = 0.771<br>\nSingle Fold Validation AUC = 0.7679</p>\n<p>I use all the train data, but I think it does not need to use all.</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 1101552,
      "author_name": "yangxiaoshuai",
      "author_url": "",
      "post_date": "12/04/2020 02:30:16",
      "content": "<p>The best single model score I've seen is LB0.801, awesome!<br>\nthis<a href=\"url\" target=\"_blank\">https://www.kaggle.com/c/riiid-test-answer-prediction/discussion/192919</a></p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 1101644,
      "author_name": "aman1391",
      "author_url": "",
      "post_date": "12/04/2020 05:15:42",
      "content": "<p>Model = LightGBM<br>\nLB : 0.769<br>\nCV : 0.7686</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 1110036,
      "author_name": "vineeth1999",
      "author_url": "",
      "post_date": "12/12/2020 11:09:15",
      "content": "<p>Model: LightGBM<br>\nLB: 0.700<br>\nCV: 0.798<br>\nI dont know what caused this much gap.</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 1118327,
      "author_name": "wuwenmin",
      "author_url": "",
      "post_date": "12/19/2020 00:28:27",
      "content": "<p>Model: LGB<br>\nLB: 0.787<br>\nCV: 0.787937, single fold</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "1100930": "Hi all, \n\nHave not seen the topic with best single model discussion so creating one here. \n\nStarting with me, I have just started working in this competition.\nModel = LGBM\nLB = 0.760\nCV = 0.755\nSingle Fold\n\nSo what is your best single model score?",
    "1101236": "just a question please ? Are you using all the train data ?",
    "1101450": "Using 10M rows to train.\n\nSingle model lgbm, single fold val.\n\nVal score: 0.765, lb score: 0.765",
    "1101548": "Model = XGB\nLB = 0.771\nSingle Fold Validation AUC = 0.7679\n\nI use all the train data, but I think it does not need to use all.",
    "1101552": "The best single model score I've seen is LB0.801, awesome!\nthis[https://www.kaggle.com/c/riiid-test-answer-prediction/discussion/192919](url)",
    "1101644": "Model = LightGBM\nLB : 0.769\nCV : 0.7686",
    "1110036": "Model: LightGBM\nLB: 0.700\nCV: 0.798\nI dont know what caused this much gap.",
    "1118327": "Model: LGB\nLB: 0.787\nCV: 0.787937, single fold"
  },
  "source": "meta"
}