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  "fetched_at": "2026-10-19T14:07:37Z",
  "source_url": "https://www.kaggle.com/competitions/dsaa-6100-movie-review-classification/data",
  "pages": [
    {
      "name": "data-description",
      "content": "## Files\n\n*   **movie_reviews.zip** - the training set\n*   **test_data.csv** - the test set\n\n\n## Columns\n\n*   ID - an anonymous id unique to a test example. This should match the ID field of the submission file. It should be in the range of 0-10,000.\n*   text - the actual sentence of each training/test example. It should be free text.\n*   label - the class label of a training example. It should be either 0 or 1.",
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      "name": "Evaluation",
      "content": "The evaluation metric for this competition is the classification accuracy score. The higher, the better.\n\nSubmission Format\nFor every question in the test data, submission files should contain two columns: Id and Category. Every line should contain two integers, separated by a comma. The first integer tells the Id of a test question (0 to 9,999), and the second integer is your prediction of its category (0 or 1).\n\nThe file should contain a header and have the following format:\n\nId,Category\n0,1\n1,1\n2,0\n3,0\n…\n9999,1",
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    {
      "name": "rules",
      "content": " - Don't cheat!\n - Apply yourself!\n - Have fun!",
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      "name": "abstract",
      "content": "This is a text classification task - sentiment classification. Every document (a line in the data file) is a movie review extracted from IMDB. Your goal is to classify the sentiment of each review into \"good\" or \"bad\".\n\nThe training data contains 40,000 reviews, already labeled with 1 (representing a \"good\" sentiment) or 0 (indicating a \"bad\" sentiment). The test data contains 10,000 reviews that are unlabeled. The submission should be a .csv (comma-separated free text) file with a header line \"Id,Category\". Each subsequent line should contain exactly two integers, separated by a comma. The first integer is the line ID of a test sentence (ranging from 0 to 9,999), and the second integer is the category your classifier predicts, either 0 or 1.\n\nYou can make 10 submissions per day. Once you submit your results, you will get an accuracy score computed based on 90% of the test data. This score will position you somewhere on the leaderboard. Once the competition ends, you will see the final accuracy computed based on 100% of the test data. The evaluation metric is accuracy - so aim for the highest score possible.",
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