{
  "fetched_at": "2026-10-20T03:29:44Z",
  "source_url": "https://www.kaggle.com/competitions/curso-ml-noviembre-2020/data",
  "pages": [
    {
      "name": "data-description",
      "content": "<h1>File descriptions</h1>\n<ul>\n<li><strong>challenge_dataset_train.csv</strong> - the training set</li>\n<li><strong>challenge_dataset_test.csv</strong> - the test set</li>\n",
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    {
      "name": "Description",
      "content": "<h1>¡Bienvenidos a la competencia de Machine Learning de la C7U!</h1>\n<p>En esta competencia vamos a estar haciendo un ejercicio de Churn. En un problema de Churn lo importante es predecir si un cliente va a abandonar mi producto/negocio antes de que suceda. Por ejemplo, en un banco el churn podría predecirse a partir de un cliente con muy pocas transacciones en su cuenta.</p>\n<h2>¿Para qué sirve predecir el churn?</h2>\n<p>Si una empresa sabe que clientes podrían abandonar el producto/servicio de manera anticipada, esto habilitaría a la empresa a realizar acciones para mantener y retener esos clientes antes de que decidan irse.</p>",
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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<h2>Submission Format</h2>\n<p>The file should contain a header and have the following format:</p>\n<pre>customerID,Churn<br>1820-DJFYT,1<br>5426-AKJHR,0<br>1856-TBHQT,0<br></pre>",
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    {
      "name": "rules",
      "content": "This is a page where you can include rules that participants must accept before joining. You may wish to include rules like:\n\n - Don't cheat!\n - Apply yourself!\n - Have fun!",
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      "hasIsPublished": false,
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}