{
  "fetched_at": "2026-10-19T17:02:17Z",
  "source_url": "https://www.kaggle.com/competitions/dsi19-oct/data",
  "pages": [
    {
      "name": "rules",
      "content": "There are some expectations, rather than rules:\n\n- Reproducibility: It should be clear, how and why you chose your model\n- Fairplay: Since the data is public, we encourage you to not use the original test-data-set (if you should find it :-)) \n- Help each other: Team Work is encouraged! Data Science and KNIME will be new to most, so use this challenge to learn and teach! 🎉",
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    {
      "name": "data-description",
      "content": "The data.zip file contains to files:\n\n- train.csv\n- test.csv\n\nThe goal is to predict the variable \"TargetComments\", thus it has be excluded from test.csv. Use this file to generate your prediction and upload the .csv as submission.",
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    {
      "name": "Description",
      "content": "## Intro to Challenge\n\nThis challenge is hosted by the [Data Science Initiative of the University of Vienna](https://univie.ac.at/dsi-students). \n\nThe Data Set contains entries of various Facebook pages, aggregated features of those pages as well as information about their posts. The goal is to predict the Number of comments of a post (Variable:\"TargetComments\") and minimise the Mean Absolute Error\n\n## The Data Set\n\nThe Data Set is taken from the [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/datasets/Facebook+Comment+Volume+Dataset), and the corresponding paper can be found here: http://uksim.info/uksim2015/data/8713a015.pdf\n\nThe dataframe however has been slightly modified for easier use.",
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    {
      "name": "Evaluation",
      "content": "## Evaluation Metrics\n\nThe Evaluation Metrics is the Mean Absolute Error between the true value and the prediction.\n\n## Submission Format\n\nThe Submission .csv must contain exactly those two Columns:\n\n1. 'row ID': containing the corresponding row ID of the test-set\n2. 'TargetComments': Containing your prediction\n\nMake sure to have those to column-names matched exactly!",
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}