{
  "fetched_at": "2026-10-20T10:14:38Z",
  "source_url": "https://www.kaggle.com/competitions/bitsf312-lab1/data",
  "pages": [
    {
      "name": "rules",
      "content": "This is a page where you can include rules that participants must accept before joining. You may wish to include rules like:\n\n - Don't cheat!\n - Apply yourself!\n - Have fun!\n\nIf anyone is found using the accounts of students not registered in the course for submission, zero will be awarded directly.",
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    {
      "name": "data-description",
      "content": "<p>This page contains two files that you are supposed to download and work on. They are as mentioned below:</p>\n<ul>\n<li><strong>train.csv</strong> - the training set</li>\n<li><strong>test.csv</strong> - the test set</li>\n<li><strong>sample_submission.csv</strong> - a sample submission file in the correct format</li>\n</ul>\n<h2>Data fields</h2>\nAll column names are self explanatory.",
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    {
      "name": "Description",
      "content": "You are given a classification dataset with 11 attributes (not counting the ID and Class). The train set contains 371 instances and the test set contains 159 instances. Your task is to classify the test set into 6 classes based on your training data.",
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      "name": "Evaluation",
      "content": "The evaluation metric for this competition is Accuracy. I don't think it necessary to provide a formula for the same.\n\n<h2>Submission Format</h2>\n<p>You need to submit classes of 159 tuples in the test dataset. The submission file must contain exactly two attributes: 'ID' of the tuples and its corresponding 'Class' label.\n\nThe submission file should contain a header and have the following format:</p>\n<pre>ID,Class<br />371,1<br /><span style=\"font-size: 14px; line-height: 1.4em;\">372,3<br />373,0<br /></span><span style=\"font-size: 14px; line-height: 1.4em;\">374,5<br /></span><span style=\"font-size: 14px; line-height: 1.4em;\">etc.</span></pre>\n\nFor your reference a sample_submission.csv has been uploaded in the Data tab that will clarify any doubt regarding submission format. \n\n<hr />\n\nYou are given 3 days with 7 submissions on each day.\n\nYour submissions will be evaluated on 70% of the test dataset to give your results on the public leaderboard. At the end of the competition, your selected submissions (you can select maximum 2 submissions) will be evaluated on rest 30% of the test dataset and will be shown on the private leaderboard. However, your final marks will be based on your performance on 100% data.\n\n<hr />\n\n<h2> Note: </h2>\n\nAFTER the competition ends, you need to upload the jupyter notebook that gave you your best result (corresponding to the public leaderboard) as a kernel on Kaggle. The result obtained on running your uploaded kernel must match your score on the private leaderboard. In case of mismatch, no marks will be awarded.",
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