{
  "fetched_at": "2026-10-20T04:02:14Z",
  "source_url": "https://www.kaggle.com/competitions/comp90049s2p2/data",
  "pages": [
    {
      "name": "data-description",
      "content": "To maintain consistency, we prefer to publish the data file only through one portal. You can find all the required files for this Assignment on LMS.",
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    {
      "name": "Description",
      "content": "This is the 2020-S2 COMP90049 playground for Assignment 2.\n\nIn this assignment, you are working on the task of music genre classification. You will test different classification algorithms, experiment with different features, and analyse your models through evaluation.\n\nYou are asked to submit your prediction on the test dataset here.\n\n### ************PLEASE ONLY USE YOUR STUDENT ID AS YOUR DISPLAY NAME.************\n**All submissions under any other display name are considered fake and will be ignored.**",
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    {
      "name": "Evaluation",
      "content": "The evaluation metric for this competition is Accuracy.\nFor every track in the dataset, submission files should contain two columns: trackId and genre class. The Class can be one of the following genre labels: 'soul and reggae', 'pop', 'punk', 'jazz and blues', 'dance and electronica', 'folk', 'classic pop and rock', and 'metal'.\nThe file should contain a header (trackId and genres), sorted based on trackId and have the following format:\n\n```\ntrackID,genre\n6732,metal\n5415,soul and reggae \n7757,pop\netc.\n```\n\nSubmissions will be evaluated and ranked by Kaggle for accuracy, against just 30% of the test data, forming the public leaderboard.",
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    {
      "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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