{
  "fetched_at": "2026-10-20T14:05:50Z",
  "source_url": "https://www.kaggle.com/competitions/alsettest/data",
  "pages": [
    {
      "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>TBA</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>2/1/2014 12:00 AM UTC</strong></p>\r\n\t<!-- End Base Rules -->\r\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": "<h2>File descriptions</h2>\n<ul>\n<li><strong>train_X.csv</strong> - features of the training set</li>\n<li><strong>train_Y.csv</strong> - Labels for the training set</li>\n<li><strong>test_X.csv</strong> - the test set</li>\n</ul>",
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    {
      "name": "Description",
      "content": "Welcome to Kaggle! Kaggle is a machine learning competition website and we've decided to leverage it to try something new for this homework. \n\nYou will be submitting the results of your classifier on Kaggle.\n\nThe classifier\n--------------\n\n \nYou'll be training a k-means classifier that will be used on a iris dataset. To actually see the results of your classifier, you'll have to submit the predictions to Kaggle, which will evaluate them and return your error rate.\n\nNote that since you don't have access to the test labels, you'll need to evaluate your classifier using cross validation.",
      "isPublished": false,
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    {
      "name": "Evaluation",
      "content": "**Please submit a CSV file formatted as follows:  \n\n```\nId petal_name   \n0 Iris-setosa   \n1 Iris-virginica  \n2 Iris-versicolor  \n3 Iris-setosa  \n4 Iris-setosa  \n...\n```  \n\nThe first line of the file should be the header \"Id\" and \"petal_name\".\nThe rest should be the predicted petal name for each sample you're classifying. ",
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}