{
  "fetched_at": "2026-10-19T22:51:11Z",
  "source_url": "https://www.kaggle.com/competitions/digitrecognizer1438/data",
  "pages": [
    {
      "name": "rules",
      "content": "\n\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>\n        Privately sharing code or data outside of teams is not permitted.\n        It's okay to share code if made available to all participants on the forums.\n    </p>\n    <h3>This is not a group assignment, everyone has to work individually</h3>\n    ",
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      "postTitle": "",
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    {
      "name": "data-description",
      "content": "<p>This is a subset of MNSIT dataset, containing only  1, 4, 3 and 9 digits, the data is given in form of feature vectors, wher features are the values of pixels</p>\n<h2>File descriptions</h2>\n<ul>\n<li><strong>trainData.csv</strong> - Feature vectors of Training data in CSV format</li>\n<li><strong>testData.csv</strong> - Feature vectors of Test data in CSV formate</li>\n<li><strong>sampleSubmission.csv</strong> - a sample submission file in the correct format(note this is just a sample the labels are not correct int this file)</li>\n<li><strong>trainLabels</strong> - Labels of training data</li>\n\n</ul>\n<h2>Data fields</h2>\n<ul>\n<li><strong>pixelNo</strong> - value of pixel in the image</li>\n<li><strong>Label</strong> -class</li>\n\n</ul>",
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    {
      "name": "Description",
      "content": "<p>This is a Digit Recognization multiclass classfication problem. The data set is a subset on MNSIT dataset, only containing images of 1, 4,3 and 9</p>\n<p>The data is given in form of feature vectors</p>\n<h2>What is it about?</h2>\n<p>\nIn this task you will see the performance of different classifier. You will train multiple classifiers and check their accuracy in different settings for this problem, some of the mandatory classifiers are </p>\n<pre>kNN, Decision trees and  Neural Networks</pre>\n<p>Once you have trained your classifier, label the test data and upload the submissions. You will be able to see you performance of public leaderboard.</p>\n\n\n\n<p>The performance of your classifier will be evaluated using accuracy:</p>\n<pre>[accuracy= number of correctly classified test instance/ total test instances]</pre>\n<p>You will upload your results, i.e labels of test data, as submissions. The accuracy shown on plublic leader board will be of 50% of the data. The accuracy for rest of the 50% of data will be on private leader board, that will be disclosed at the end of the competition.</p>\n<p>You may submit upto 50 submissions each day</p>",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "Evaluation",
      "content": "<p>The performance of your classifier will be evaluated using accuracy:</p>\n<pre>[accuracy= number of correctly classified test instance/ total test instances]</pre>\n<p>You will upload your results, i.e labels of test data, as submissions. The accuracy shown on plublic leader board will be of 50% of the data. The accuracy for rest of the 50% of data will be on private leader board, that will be disclosed at the end of the competition.</p>",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    }
  ]
}