{
  "fetched_at": "2026-10-19T12:44:56Z",
  "source_url": "https://www.kaggle.com/competitions/airbnb-price-prediction/data",
  "pages": [
    {
      "name": "data-description",
      "content": "Airbnb, Inc. is an American company operating an online marketplace for short- and long-term homestays and experiences. This dataset offers a detailed overview of Airbnb listings spanning diverse locations, providing information on property features, pricing, reviews, and host characteristics. \n\n## Files\n\n*   **Airbnb_train.csv** - the training set\n*   **Airbnb_test.csv** - the test set\n*   **sample_submission.csv** - a sample submission file in the correct format\n\n## Columns\n\n*   `id` - listing id\n*   `property_type` - Property type\n*   `room_type` - Room type\n*   `amenities` - Amenities of the Airbnb\n*   `accommodates` - Number of accommodations\n*   `bathrooms` - Number of bathrooms\n*   `bed_type` - Type of bed\n*   `cancellation_policy` - Cancellation policies\n*   `cleaning_fee` - Cleaning fees\n*   `city` - City\n*   `description` - Description\n*   `first_review` - Date of the first review\n*   `host_has_profile_pic` - If the host has profile pictures\n*   `host_identity_verified` - If the identity of the host has been verified\n*   `host_response_rate` - Percentage of reviews that have been responded by the host\n*   `host_since` - Date since which the host started renting on Airbnb\n*   `instant_bookable` - Bookable instantly\n*   `last_review` - Date of the last review\n*   `latitude` - Latitude\n*   `longitude` - Longitude\n*   `name` - Name of the listing\n*   `neighbourhood` - Neighbourhood\n*   `number_of_reviews` - Number of reviews\n*   `review_scores_rating` - Average review scores\n*   `thumbnail_url` - URL of the thumbnail\n*   `zipcode` - Zipcode\n*   `bedrooms` - Number of bedrooms\n*   `beds` - Number of beds",
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    {
      "name": "Evaluation",
      "content": "Submissions are evaluated on [Root Mean Squared Error (RMSE)](https://en.wikipedia.org/wiki/Root-mean-square_deviation) between the predicted prices and the observed prices.\n\n\n## Submission File\nFor every listing in the test dataset, the submission file should contain two columns: id and price, i.e. the id and the predicted price for the listing.\n\nThe file should contain a header and have the following format:\n\n    id,price\n    13055,110\n    2970,80\n    27364,60\n    etc.",
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    {
      "name": "rules",
      "content": "<h3>Team Limits</h3>\n<p>Each team is limited to have no more than <strong>3</strong> persons.</p>\n<h3>Submission Limits</h3>\n<p>You may submit a maximum of <strong>20</strong> entries per day.</p>\n<p>You may select up to <strong>3</strong> final submissions for judging.</p>",
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    {
      "name": "abstract",
      "content": "This competition is an in-class competition for the course, \"Artificial Intelligence and Machine Learning (Spring 2024)\", in Renmin University of China.\n\nThe competition is to predict the rental prices for listings on the Airbnb website.",
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