{
  "id": 1305,
  "title": "capped binomial problem",
  "url": "/competitions/WhatDoYouKnow/discussion/1305",
  "author_name": "",
  "post_date": "2012-01-27T18:10:19.837Z",
  "votes": null,
  "comment_count": 4,
  "views": 2458,
  "content": "<p>Hello,</p>\r\n<p>We have the problem with the following:</p>\r\n<p>When we perform the learning, and calculate the capped binomial we get one value, which is pretty good. However, when we submit this result, its value on the website is different, much worse. This isn't an unique case, we tried testing our learning algorithm\r\n with different datasets and obtained the capped binomial around 0.25 and it varied very little for those different datasets. When we submitted these results, on the website it was around 0.31</p>\r\n<p>We checked our capped binomial calculation function with the example given online (chess competition) and it was ok.</p>\r\n<p>We think it could be connected with the way of submitting the results. Does anyone have any&nbsp;idea what could be the problem?</p>\r\n<p>TIA</p>",
  "messages": [
    {
      "id": "8283",
      "postDate": "01/27/2012 18:10:19",
      "content": "<p>Hello,</p>\r\n<p>We have the problem with the following:</p>\r\n<p>When we perform the learning, and calculate the capped binomial we get one value, which is pretty good. However, when we submit this result, its value on the website is different, much worse. This isn't an unique case, we tried testing our learning algorithm\r\n with different datasets and obtained the capped binomial around 0.25 and it varied very little for those different datasets. When we submitted these results, on the website it was around 0.31</p>\r\n<p>We checked our capped binomial calculation function with the example given online (chess competition) and it was ok.</p>\r\n<p>We think it could be connected with the way of submitting the results. Does anyone have any&nbsp;idea what could be the problem?</p>\r\n<p>TIA</p>",
      "rawMarkdown": "",
      "votes": null
    },
    {
      "id": "8285",
      "postDate": "01/27/2012 19:27:27",
      "content": "<p>Are you getting 0.25 on cross-validation of the training data? It's possible you've got a model that's overfitting and does not generalize well.</p>",
      "rawMarkdown": "",
      "votes": null
    },
    {
      "id": "8290",
      "postDate": "01/27/2012 20:52:27",
      "content": "<p>Additionally, the submission set is not a random sample of the whole training set. It's substantially different in makeup due to being the final answer from users with robust history.</p>",
      "rawMarkdown": "",
      "votes": null
    },
    {
      "id": "8306",
      "postDate": "01/28/2012 10:58:07",
      "content": "<p>[quote=Momchil Georgiev;8285]</p>\r\n<p>Are you getting 0.25 on cross-validation of the training data? It's possible you've got a model that's overfitting and does not generalize well.</p>\r\n<p>[/quote]</p>\r\n<p>Yes, I obtain also a result around this same value for the validation test set which has&nbsp;a constitution similar to the one of the test set&nbsp; regarding to the game types and subtracks. And it's consistent with the results I obtain with other datasets.</p>\r\n<p>So thank you&nbsp;for trying to understand my problem but this cannot be the error.</p>",
      "rawMarkdown": "",
      "votes": null
    },
    {
      "id": "8360",
      "postDate": "01/31/2012 04:37:19",
      "content": "<p>I had a&nbsp;very similar problem which was caused by accidently using columns from test.csv that were different from what I used to train the model.&nbsp; Hope this helps!</p>",
      "rawMarkdown": "",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 8285,
      "author_name": "sirguessalot",
      "author_url": "",
      "post_date": "01/27/2012 19:27:27",
      "content": "<p>Are you getting 0.25 on cross-validation of the training data? It's possible you've got a model that's overfitting and does not generalize well.</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 8290,
      "author_name": "biasvariance",
      "author_url": "",
      "post_date": "01/27/2012 20:52:27",
      "content": "<p>Additionally, the submission set is not a random sample of the whole training set. It's substantially different in makeup due to being the final answer from users with robust history.</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 8306,
      "author_name": "thomasgenevois",
      "author_url": "",
      "post_date": "01/28/2012 10:58:07",
      "content": "<p>[quote=Momchil Georgiev;8285]</p>\r\n<p>Are you getting 0.25 on cross-validation of the training data? It's possible you've got a model that's overfitting and does not generalize well.</p>\r\n<p>[/quote]</p>\r\n<p>Yes, I obtain also a result around this same value for the validation test set which has&nbsp;a constitution similar to the one of the test set&nbsp; regarding to the game types and subtracks. And it's consistent with the results I obtain with other datasets.</p>\r\n<p>So thank you&nbsp;for trying to understand my problem but this cannot be the error.</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 8360,
      "author_name": "chaseos",
      "author_url": "",
      "post_date": "01/31/2012 04:37:19",
      "content": "<p>I had a&nbsp;very similar problem which was caused by accidently using columns from test.csv that were different from what I used to train the model.&nbsp; Hope this helps!</p>",
      "votes": null,
      "replies": []
    }
  ],
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}