{
  "fetched_at": "2026-10-20T10:06:59Z",
  "source_url": "https://www.kaggle.com/competitions/dsba6156-1/data",
  "pages": [
    {
      "name": "rules",
      "content": "Each member of the class is competing against every other member of the class.  Your work is expected to be your own.  This is not a team activity.\n\nTo be succinct:\n\n* Don't cheat!\n* Apply yourself!\n* Have fun!",
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    {
      "name": "data-description",
      "content": "# Data Files\n* train_X.csv - This is the file of features that you will train your model against.\n* train_Y.csv - This is the file of labels for each row in the training set.\n* test_X.csv - This is the data that you will create your submission against.",
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    {
      "name": "Description",
      "content": "This is our first Kaggle competition for this semester.  For this competition, you will work individually and develop a SVM program to optimally separate each of the three classes in the data.  Once you have successfully trained your model, you will submit a dataset for your program executed against the provided test dataset.",
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    {
      "name": "Evaluation",
      "content": "<h2>Submission Format</h2>\n<p><strong>For every row in the test dataset</strong>, submission files should contain two columns: idx and t1.   The output file should be comma-delimited, and the format should match the format of the train_Y.csv file provided.",
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}