{
  "fetched_at": "2026-10-19T17:33:49Z",
  "source_url": "https://www.kaggle.com/competitions/cme250-final-project/data",
  "pages": [
    {
      "name": "data-description",
      "content": "We have two files, **train.csv** contains the training data which contains the feature and target of each observation, **test.csv** contains the features of the test data (but not the target, which you must predict).\n\n## Files\n\n*   **train.csv** - the training set\n*   **test.csv** - the test set\n*   **sample_submission.csv** - a sample submission file in the correct format\n\n## Columns\n\n*   `class` - whether the patient progressed to Severe Dengue or not\n*   `dataset` - the dataset cohort used to collect this observation\n*  `SampleID` - the ID for the observation",
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    {
      "name": "Description",
      "content": "For the final project of CME250, you will be predicting whether patients will progress to Severe Dengue.\n\nPatients come from 11 different dataset cohorts. For testing, we reserve two of those cohorts. Although it is not necessary, we recommend that in any validation (or cross validation), cohorts be separated.\n\nWe thank Yiran Liu for providing this dataset.",
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    {
      "name": "Evaluation",
      "content": "The evaluation metric for this competition is the Area Under the ROC Curve [AUC](https://en.wikipedia.org/wiki/Receiver_operating_characteristic). \n\n## Submission Format\n\nThe submission file should be a csv that contains two columns: `SampleID` and `class`. `class` should be a probability, i.e., a number between zero and one.\n\nThe file should contain a header and have the following format:\n```\nSampleID,class\nGSM1071039,0.79\n```",
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    {
      "name": "rules",
      "content": "You can make groups of up to two people if you want",
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}