{
  "fetched_at": "2026-10-19T18:51:49Z",
  "source_url": "https://www.kaggle.com/competitions/fxx-test/data",
  "pages": [
    {
      "name": "rules",
      "content": "<!-- Begin Base Rules -->\n<h3>One account per participant</h3>\n<p>You cannot sign up to Kaggle from multiple accounts and therefore you cannot submit from multiple accounts.</p>\n<h3>No private sharing outside teams</h3>\n<p>Privately sharing code or data outside of teams is not permitted. It's okay to share code if made available to all participants on the forums.</p>\n<h3>Team Mergers</h3>\n<p>Team mergers are not allowed in this competition.</p>\n<h3>Team Limits</h3>\n<p>There is no maximum team size.</p>\n<h3>Submission Limits</h3>\n<p>You may submit a maximum of 2 entries per day.</p>\n<p>You may select up to 2 final submissions for judging.</p>\n<h3>Competition Timeline</h3>\n<p>Start Date: <strong>2018-03-21</strong></p>\n<p>Merger Deadline: <strong>None</strong></p>\n<p>Entry Deadline: <strong>None</strong></p>\n<p>End Date: <strong>2018-06-30 00:00:00</strong></p>\n<!-- End Base Rules -->\n<p>The rules page is a bit special: it will auto-update the text based on the parameters of the competition. The rules you need to add here are any additional rules relating to dataset usage. You may also put grading information here.</p>",
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    {
      "name": "data-description",
      "content": "<p>You are given three files:</p>\n<p>1.save_train.csv</p>\n<p>The format of each line is as follows:</p>\n<pre>id,value0,value1,...,value383,reference</pre>\n<p>where value0,value1,...,value383 are the features.</p>\n<p>2.save_test.csv</p>\n<p>This file contains the features whose references you need to predict. The format of each line is as follows:</p>\n<pre>id,value0,value1,...,value383</pre>\n<p>3.sample_submission.csv</p>\n<p>The file you submit should have the same format as this file,the format of each line is as follows:</p>\n<pre>id,reference</pre>",
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    },
    {
      "name": "Description",
      "content": "<p>This is a project of the Data Mining course (instructor: Dr. Yan Pan) in 2018 for the students in School of Data and Computer Science, Sun Yat-sen University.</p>\n<p>This is a linear regression task. Please use what you have learned from our course and write an algorithm to train a regressor.</p>\n<p>Have fun!</p>",
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    },
    {
      "name": "Evaluation",
      "content": "\n<p>The evaluation metric for this competition is RMSE (Root Mean Squared Error).</p>\n<p>The file should contain a header and have the following format:</p>\n<p>id,reference<br />0,20.1<br />1,1.232<br />2,1.3<br />3,0.855<br />etc.</p>",
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}