{
  "fetched_at": "2026-10-19T19:57:22Z",
  "source_url": "https://www.kaggle.com/competitions/CS98-22-DL-Task1/data",
  "pages": [
    {
      "name": "data-description",
      "content": "The training and test sets are provided below.",
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    {
      "name": "Evaluation",
      "content": "We use LogLoss for evaluation. \n\nSubmission Format\nFor every document, the submission files should contain two columns: id, and diagnosis, where the diagnosis is the probability of malignant(which is 1 in training data). See sample submission in the data section.",
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    {
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    {
      "name": "Description",
      "content": "This task is to classify tumours into Malignant or Benign type when provided with the tumour's attributes in the dataset. The problems can be solved using Python, TensorFlow and Keras along with any other packages. You can also use PyTorch. \n\nMore information about the data can be found at: https://archive.ics.uci.edu/ml/datasets/breast+cancer+wisconsin+(diagnostic) \nNOTE:  The coursework will use a different datasets but with very similar attributes to the above. ",
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