{
  "fetched_at": "2026-10-24T12:06:57Z",
  "source_url": "https://www.kaggle.com/competitions/dm-assignment-1/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!",
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      "content": "<p>This page contains two files that you are supposed to download and work on. They are as mentioned below:</p>\n<h2>File descriptions</h2>\n<ul>\n<li><strong>dataset.csv</strong> - the entire dataset</li>\n<li><strong>sample_submission.csv</strong> - a sample submission file in the correct format</li>\n</ul>",
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      "name": "Description",
      "content": "<p>This is the home page of the competition. As the description of the competition suggests you are given a dataset with 24 attributes and 1031 instances and your task is to classify the given dataset into 3 classes [0,1,2] using only <strong>Clustering</strong> algorithms. </p>\n<h2>A Brief Overview of Dataset</h2>\n<p>The given dataset contains the following 24 attributes:</p>\n<p><strong>id:</strong> Unique identity number</p>\n<p><strong>Account1:</strong> Accounts of type-1</p>\n<p><strong>Monthly Period:</strong> Duration in month</p>\n<p><strong>History:</strong> Types of client histories</p>\n<p><strong>Motvie:</strong> Types of client motives</p>\n<p><strong>Credit1:</strong> Credit amount</p>\n<p><strong>Account2:</strong> Accounts of type-2</p>\n<p><strong>Employment Period:</strong> Time Period of workers' employments</p>\n<p><strong>InstallmentRate:</strong> self-explanatory</p>\n<p><strong>Gender&Type:</strong> self-explanatory</p>\n<p><strong>Sponsors:</strong> Types of sponsors</p>\n<p><strong>Tenancy Period:</strong> Residence period</p>\n<p><strong>Plotsize:</strong> self-explanatory</p>\n<p><strong>Age:</strong> self-explanatory</p>\n<p><strong>Plan:</strong> Type of plan action</p>\n<p><strong>Housing:</strong> Type of residence owned</p>\n<p><strong>#Credits:</strong> Rate of credits</p>\n<p><strong>Post:</strong> His/Her job post</p>\n<p><strong>#Authorities:</strong> Total number of authorities engaged</p>\n<p><strong>Phone:</strong> If phone is available or not</p>\n<p><strong>Expatriate:</strong> Is he/she working for a foreign agency</p>\n<p><strong>InstallmentCredit:</strong> Credit received for installment</p>\n<p><strong>Yearly Period:</strong> Duration in years</p>\n<p><strong>Class:</strong> Target variable</p>",
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      "name": "Evaluation",
      "content": "<h2>Submission Format</h2>\n<p>You need to submit classes of 856 tuples which are not labelled in the dataset. The submission file must contain exactly two attributes: 'id' of the tuples and its corresponding 'Class' label.</p> \n<p>The submission file should contain a header and have the following format:</p>\n<pre>id,Class<br />id344,0<br /><span style=\"font-size: 14px; line-height: 1.4em;\">id744,1<br />id213,2<br /></span><span style=\"font-size: 14px; line-height: 1.4em;\">id949,1<br /></span><span style=\"font-size: 14px; line-height: 1.4em;\">etc.</span></pre>\n<p> For your reference a sample_submission.csv has been uploaded in the Data tab that will clarify any doubt regarding submission format.  </p>\n<hr />\n<p>You are given 5 days with 5 submissions on each day.</p>\n<p>Your submissions will be evaluated on 50% of the dataset to give your results on the public\nleaderboard. At the end of the competition, your selected submissions (you can select\nmaximum 2 submissions) will be evaluated on rest 50% of the data and will be shown on the\nprivate leaderboard. However, the final score will be based on your performance on 100%\ndata.</p>\n<p>The evaluation metric for this competition is <strong>Accuracy</strong>. The <strong>Accuracy</strong> score is given by:  \\[\\frac{\\#CorrectPredictions}{Total Labels(856)}\\] </p>\n<p><h2>Note:</h2> <strong>AFTER<strong> the competition ends, you need to upload the jupyter notebook that gave you your best result (corresponding to the private 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.</p>",
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