{
  "fetched_at": "2026-10-19T13:34:52Z",
  "source_url": "https://www.kaggle.com/competitions/fillthevoid-detect-digit/data",
  "pages": [
    {
      "name": "data-description",
      "content": "Columns:\n\nThe train.csv file must have a column named \"label\" representing the true digit label for each image.\nThe test.csv file must have an additional column named \"id\" to uniquely identify each test image.\nPixel Values:\n\nPixel values for each image are provided in separate columns following the label column in train.csv and without label column in test.csv.\nPixel values should be used for model training and prediction. The image is assumed to be square, with equal height and width.",
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      "postTitle": "",
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    {
      "name": "Evaluation",
      "content": "Model Selection:\n\nParticipants are free to use any machine learning or deep learning model to train on the provided training data.\nTransfer learning from pre-trained models is allowed.\nCross-validation:\n\nParticipants are encouraged to use cross-validation techniques to evaluate the performance of their models.\nEvaluation Metric:\n\nThe competition will be evaluated based on a predefined metric (e.g., accuracy, F1 score) to measure the model's ability to correctly classify digits.",
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    },
    {
      "name": "rules",
      "content": "- Participants are expected to adhere to ethical guidelines during the competition.\n- Any form of cheating, plagiarism, or unethical behavior will result in disqualification.",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
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    },
    {
      "name": "abstract",
      "content": "**Objective:**\n\nThe goal of the competition is to develop a machine learning model capable of accurately predicting the digit label based on the pixel values provided in the train.csv and test.csv files.\n\n**Data Description:**\nThe training dataset (train.csv) contains labeled examples of digits, with each row representing a unique digit image.\nThe test dataset (test.csv) contains digit images without labels. Participants are required to predict the label for each test image.",
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      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    }
  ]
}