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  "fetched_at": "2026-10-20T09:57:55Z",
  "source_url": "https://www.kaggle.com/competitions/2403-boston-housing-dataset/data",
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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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      "content": "CRIM：per capita crime rate by town<br>\nZN：proportion of residential land zoned for lots over 25,000 sq.ft.<br>\nINDUS：proportion of non-retail business acres per town<br>\nCHAS：Charles River dummy variable (= 1 if tract bounds river; 0 otherwise)<br>\nNOX：nitric oxides concentration (parts per 10 million)<br>\nRM：average number of rooms per dwelling<br>\nAGE：proportion of owner-occupied units built prior to 1940<br>\nDIS：weighted distances to five Boston employment centres<br>\nRAD：index of accessibility to radial highways<br>\nTAX：full-value property-tax rate per $10,000<br>\nPTRATIO：pupil-teacher ratio by town<br>\nB：1000(Bk - 0.63)^2 where Bk is the proportion of blacks by town<br>\nLSTAT：% lower status of the population<br>\nMEDV：Median value of owner-occupied homes in $1000's<br>",
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      "name": "Description",
      "content": "# Description\nThis dataset contains information collected by the U.S Census Service concerning housing in the area of Boston Mass. It was obtained from the StatLib archive, and has been used extensively throughout the literature to benchmark algorithms. However, these comparisons were primarily done outside of Delve and are thus somewhat suspect. The dataset is small in size with only 506 cases.\n\n# Source\n[www.cs.toronto.edu](https://www.cs.toronto.edu/~delve/data/boston/bostonDetail.html)\n\nThe data was originally published by Harrison, D. and Rubinfeld, D.L. `Hedonic prices and the demand for clean air', J. Environ. Economics & Management, vol.5, 81-102, 1978.\n\n# Dataset Naming\n\nThe name for this dataset is simply boston. It has two prototasks: nox, in which the nitrous oxide level is to be predicted; and price, in which the median value of a home is to be predicted\n\n# Introduction of the 24 datasets\nFollowing **24 Ultimate Data Science Projects To Boost Your Knowledge and Skills** [[Link]](https://www.analyticsvidhya.com/blog/2018/05/24-ultimate-data-science-projects-to-boost-your-knowledge-and-skills/). We will go through a sequence of classic data science projects to increase our skill\n",
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    {
      "name": "Evaluation",
      "content": "The evaluation metric for this competition is RMSE. \nFor more information about RMSE, please visit [WIKI](https://en.wikipedia.org/wiki/Root-mean-square_deviation)",
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