{
  "fetched_at": "2026-10-20T02:33:12Z",
  "source_url": "https://www.kaggle.com/competitions/cp-ds-guild/data",
  "pages": [
    {
      "name": "rules",
      "content": " - Don't cheat!\n - Apply yourself!\n - Have fun!",
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    {
      "name": "data-description",
      "content": "\n<h2>CP Competition - Training and Test files descriptions</h2>\n<ul>\n\n<ul>\n<li><strong>challenge_train.csv</strong> - the training set</li>\n<li><strong>challenge_test.csv</strong> - the test set</li>\n<li><strong>sampleSubmission.csv</strong> - a sample submission file in the correct format</li>\n<li>etc...</li>\n</ul>\n<h2>Data fields</h2>\n<ul>\n<li><strong>imdbID</strong> - an anonymous id unique to a given a movie</li>\n<li><strong>Plot</strong> - Movie plot</li>\n<li><strong>label</strong> - the main Genre of the movie</li>\n<li>etc...</li>\n</ul>",
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    {
      "name": "Description",
      "content": "<h2>Check Point in house Data Science Guild Competition</h2>\n<p>Detect the movie Genre according to the Plot text\nFeel free to use any ML techniques you wish to try out. Do your best in competing, learning and experimenting.</p><br>\nThe rules are simple:  <br>\nDon't cheat!\nApply yourself! \nHave fun!\n<img src=\"http://flovv.github.io/figures/post25/imdb_classification.png\">\n<p></p><h2>Acknowledgements</h2>\n<p>We thank IMDB for providing this dataset.</p>\n\n\n  [1]: http://flovv.github.io/figures/post25/imdb_classification.png",
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    {
      "name": "Evaluation",
      "content": "<p>The evaluation metric for this competition is <a href=\"https://www.kaggle.com/wiki/MeanFScore\"> Mean F1-Score</a>. The F1 score, commonly used in information retrieval, measures accuracy using the statistics precision p and recall r. Precision is the ratio of true positives (tp) to all predicted positives (tp + fp). Recall is the ratio of true positives to all actual positives (tp + fn). The F1 score is given by:</p>\n<p>\\[ F1 = 2\\frac{p \\cdot r}{p+r}\\ \\ \\mathrm{where}\\ \\ p = \\frac{tp}{tp+fp},\\ \\ r = \\frac{tp}{tp+fn} \\]</p>\n<p>The F1 metric weights recall and precision equally, and a good retrieval algorithm will maximize both precision and recall simultaneously. Thus, moderately good performance on both will be favored over extremely good performance on one and poor performance on the other.</p>\n\n<pre>imdbID, Prediction<br>tt0918940, Drama<br></pre>",
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