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  "source_url": "https://www.kaggle.com/competitions/glioma-survival-predictions/data",
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      "name": "data-description",
      "content": "<h2>File descriptions</h2>\r\n<ul>\r\n<li><strong>GlioblastomaWide.csv</strong> - the training set</li>\r\n<li><strong>final.csv</strong> - the test set - this set should be used for scoring</li>\r\n<li><strong>example.csv</strong> - a sample submission file in the correct format, see https://inclass.kaggle.com/c/glioma-survival-predictions/details/evaluation for more details</li>\r\n<li></li>\r\n</ul>",
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      "content": "<p>Training: a dataset with RNAseq data for Glioma cancers, one year survival, age and few other variables. All together 125 rows</p>\r\n<p>Test: 250 cancer patients for Glioma cancers, you are expected to find one year prediction scores. Scores can be a single digit (0/1) or a real number</p>\r\n<h2></h2>",
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      "name": "Evaluation",
      "content": "<p>The evaluation metric for this competition is <a href=\"https://www.kaggle.com/wiki/MeanFScore\"> Mean F1-Score</a>. The F1 score, commonly used in information retrieval, measures accuracy using the statistics precision p and recall r. Precision is the ratio of true positives (tp) to all predicted positives (tp + fp). Recall is the ratio of true positives to all actual positives (tp + fn). The F1 score is given by:</p>\r\n<p>\\[ F1 = 2\\frac{p \\cdot r}{p+r}\\ \\ \\mathrm{where}\\ \\ p = \\frac{tp}{tp+fp},\\ \\ r = \\frac{tp}{tp+fn} \\]</p>\r\n<p>The F1 metric weights recall and precision equally, and a good retrieval algorithm will maximize both precision and recall simultaneously. Thus, moderately good performance on both will be favored over extremely good performance on one and poor performance on the other.</p>\r\n<h2>Submission Format</h2>\r\n<p><strong>For every paient in the test dataset</strong>, submission files should contain two columns: rowid and Expected - the score for 1 year survival</p>\r\n<p>The file should contain a header and have the following format:</p>\r\n<pre>rowid,Expected<br />1,1<br /><span style=\"font-size: 14px; line-height: 1.4em;\">2,0<br />3,1<br /></span><span style=\"font-size: 14px; line-height: 1.4em;\">4,1<br /></span><span style=\"font-size: 14px; line-height: 1.4em;\">etc.</span></pre>",
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    {
      "name": "rules",
      "content": "\r\n\t<!-- Begin Base Rules -->\r\n    <h3>One account per participant</h3>\r\n    <p>You cannot sign up to Kaggle from multiple accounts and therefore you cannot submit from multiple accounts.</p>\r\n    <h3>No private sharing outside teams</h3>\r\n    <p>\r\n        Privately sharing code or data outside of teams is not permitted.\r\n        It's okay to share code if made available to all participants on the forums.\r\n    </p>\r\n    <h3>Team Mergers</h3>\r\n    <p>Team mergers are not allowed in this competition.</p>\r\n\r\n    <h3>Team Limits</h3>\r\n    <p>There is no maximum team size.</p>\r\n    <h3>Submission Limits</h3>\r\n    <p>You may submit a maximum of 2 entries per day.</p>\r\n    <p>You may select up to 2 final submissions for judging.</p>\r\n    <h3>Competition Timeline</h3>\r\n    <p>Start Date: <strong>11/7/2016 8:50 PM UTC</strong></p>\r\n    <p>Merger Deadline: <strong>None</strong></p>\r\n    <p>Entry Deadline: <strong>None</strong></p>\r\n    <p>End Date: <strong>12/7/2016 11:59 PM UTC</strong></p>\r\n\t<!-- End Base Rules -->\r\n",
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