{
  "fetched_at": "2026-10-24T23:15:26Z",
  "source_url": "https://www.kaggle.com/competitions/applications-of-machine-learningprml/data",
  "pages": [
    {
      "name": "data-description",
      "content": "Data Set Information:\n\nThis is a multilabel classification dataset. \n\nDATA\n\nThe dataset contains 3 attributes (id, commenttext, prediction) with 6 labels in prediction to classify. There were two files in the dataset train (containing 111723 samples) and test (containing 47848 samples).",
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    {
      "name": "Description",
      "content": "Multilabel Classifcation \n\nWhat do you have to do\nYou are required to use the training datasets to train the model to identify patterns that predict default. Apply the model on the testing dataset.",
      "isPublished": false,
      "hasIsPublished": false,
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    {
      "name": "Evaluation",
      "content": "The evaluation metric for this assignment is Mean F1-Score. The F1 score, commonly used in information retrieval, measures accuracy using the statistics precision p and recall r. Precision is the ratio of true positives (tp) to all predicted positives (tp + fp). Recall is the ratio of true positives to all actual positives (tp + fn). The F1 score is given by:\n\n𝐹1=2𝑝⋅𝑟𝑝+𝑟  where  𝑝=𝑡𝑝𝑡𝑝+𝑓𝑝,  𝑟=𝑡𝑝𝑡𝑝+𝑓𝑛\nThe F1 metric weights recall and precision equally, and a good retrieval algorithm will maximize both precision and recall simultaneously. Thus, moderately good performance on both will be favored over extremely good performance on one and poor performance on the other.\n\nSubmission Format\nFor every image in the dataset, submission files should contain two columns: Id and Prediction. Prediction should be comma separated. \n\nFor example\n\nID  Prediction\n0    1,1,1,1,1,1\n1     0,0,0,0,0,0",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
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    },
    {
      "name": "rules",
      "content": "Rules and Guidelines\n\n1) You must be a student of IIT Jodhpur enrolled in PRML course for 2021-22 session.\n\n2) No plagiarism is tolerated\n\n3) You can make max 5 submission for a day.",
      "isPublished": false,
      "hasIsPublished": false,
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    }
  ]
}