{
  "fetched_at": "2026-10-20T10:49:35Z",
  "source_url": "https://www.kaggle.com/competitions/aptos/data",
  "pages": [
    {
      "name": "rules",
      "content": "<!-- Begin Base Rules -->\n    <h3>One account per participant</h3>\n    <p>You cannot sign up to Kaggle from multiple accounts and therefore you cannot submit from multiple accounts.</p>\n    <h3>No private sharing outside teams</h3>\n    <p>\n        Privately sharing code or data outside of teams is not permitted.\n        It's okay to share code if made available to all participants on the forums.\n    </p>\n    <h3>Team Mergers</h3>\n    <p>Team mergers are not allowed in this competition.</p>\n\n    <h3>Team Limits</h3>\n    <p>There is no maximum team size.</p>\n    <h3>Submission Limits</h3>\n    <p>You may submit a maximum of 2 entries per day.</p>\n    <p>You may select up to 2 final submissions for judging.</p>\n    <h3>Competition Timeline</h3>\n    <p>Start Date: <strong>TBA</strong></p>\n    <p>Merger Deadline: <strong>None</strong></p>\n    <p>Entry Deadline: <strong>None</strong></p>\n    <p>End Date: <strong>2/1/2014 12:00 AM UTC</strong></p>\n\t<!-- End Base Rules -->\n<p>The rules page is a bit special: it will auto-update the text based on the parameters of the competition. The rules you need to add here are any additional rules relating to dataset usage. You may also put grading information here.</p>",
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    {
      "name": "data-description",
      "content": "<p>Aquí se muestran los archivos y las variables que componen las bases de datos. </p>\n<h2>Descripción de los archivos</h2>\n<ul>\n<li><strong>train.csv</strong> - the training set</li>\n<li><strong>test.csv</strong> - the test set</li>\n<li><strong>sampleSubmission.csv</strong> - a sample submission file in the correct format. </li>\n</ul>\n<h2>Descripción de las variables</h2>\n<ul>\n<li><strong>precio</strong> - corresponde al precio del apartamento en millones de pesos colombianos.</li>\n<li><strong>mt2</strong> - área del apartamento en metros cuadrados.</li>\n<li><strong>alcobas</strong> - número de alcobas del apartamento.</li>\n<li><strong>banos</strong> - número de baños del apartamento.</li>\n<li><strong>administracion</strong> - valor de servicio de administración del apartamento en pesos colombianos.</li>\n</ul>\n\n\n  [1]: http://fhernanb.github.io",
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    {
      "name": "Description",
      "content": "<h2>Descripción de la actividad</h2>\n<p>En esta actividad cada estudiante debe usar los datos del conjunto de entrenamiento (train.csv) para entrenar el modelo de regresión que luego se usará para predecir el precio de los apartamentos dadas las covariables en el conjunto de prueba (test.csv).</p>\n\n",
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      "hasIsPublished": false,
      "postTitle": "",
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    },
    {
      "name": "Evaluation",
      "content": "<p>La evaluación del modelo de regresión propuesto se realizará por medio del root mean square error (RMSE) que se define como:</p>\n<p>\\[ RMSE = \\sqrt{\\frac{1}{n}\\sum_{t=1}^{n}(\\hat{y}_i-y_i)^2} \\]</p>\n",
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