{
  "fetched_at": "2026-10-19T22:52:08Z",
  "source_url": "https://www.kaggle.com/competitions/competencia-clasificacin-sl/data",
  "pages": [
    {
      "name": "data-description",
      "content": "<h2>File descriptions</h2>\n<ul>\n<li><strong>TrainClas.xlsx</strong> - the training set</li>\n<li><strong>TestClas.xlsx</strong> - the test set</li>\n<li><strong>DataDes.txt</strong> - supplemental information about the data</li>\n",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
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    },
    {
      "name": "Description",
      "content": "<p>El proyecto consiste en predecir los diferentes perfiles de sus clientes de tarjetas de crédito,\ncon el propósito de poder implementar las políticas de mitigación del riesgo apropiadas para el\nproducto. En este orden de ideas, el interés principal del proyecto es poder modelar la probabilidad\nde que un cliente entre en default (imposibilidad para pagar la deuda adquirida), teniendo en\ncuenta su información financiera, comportamiento crediticio e información demográfica. El banco\ncuenta con la siguiente información para sus clientes del año 2017 La variable de respuesta es\ndefault.payment.next.month, que es igual a 1 si existe default y 0 de lo contrario.</p>",
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      "hasIsPublished": false,
      "postTitle": "",
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    },
    {
      "name": "Evaluation",
      "content": "<p>The evaluation metric for this competition is AUC. The AUC is a commonly used evaluation metric for binary problems like this one. The interpretation is that given a random positive observation and negative observation, the AUC gives the proportion of the time you guess which is which correctly. It is less affected by sample balance than accuracy. A perfect model will score an AUC of 1, while random guessing will score an AUC of around of 0.5.</p>\n<h2>Submission Format</h2>\n<p><strong>For every observation in the dataset, submission files should contain two columns: Id and Probability. The submission should be a csv file. The Id should just be the corresponding observation Id column from the dataset. The Probability column should be the predicted probability of the outcome 1 for that observation Id.\n\nThe file should contain a header and have the following format:.</strong></p><strong>\n<p>The file should contain a header and have the following format:</p>\n<pre>Id,Probability<br>1,0.8<br></pre></strong>",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
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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 - Don't cheat!",
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      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    }
  ]
}