{
  "fetched_at": "2026-10-20T02:58:41Z",
  "source_url": "https://www.kaggle.com/competitions/ames-day3/data",
  "pages": [
    {
      "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": "### Data Field Description \n\nHere's a brief version of what you'll find in the data description file.\n\n- SalePrice - the property's sale price in dollars. This is the target variable that you're trying to predict.\n- MSSubClass: The building class\n- MSZoning: The general zoning classification\n- LotFrontage: Linear feet of street connected to property\n- LotArea: Lot size in square feet\n- Street: Type of road access\n- Alley: Type of alley access\n- LotShape: General shape of property\n- LandContour: Flatness of the property\n- Utilities: Type of utilities available\n- LotConfig: Lot configuration\n- LandSlope: Slope of property\n- Neighborhood: Physical locations within Ames city limits\n- Condition1: Proximity to main road or railroad\n- Condition2: Proximity to main road or railroad (if a second is present)\n- BldgType: Type of dwelling\n- HouseStyle: Style of dwelling\n- OverallQual: Overall material and finish quality\n- OverallCond: Overall condition rating\n- YearBuilt: Original construction date\n- YearRemodAdd: Remodel date\n- RoofStyle: Type of roof\n- RoofMatl: Roof material\n- Exterior1st: Exterior covering on house\n- Exterior2nd: Exterior covering on house (if more than one material)\n- MasVnrType: Masonry veneer type\n- MasVnrArea: Masonry veneer area in square feet\n- ExterQual: Exterior material quality\n- ExterCond: Present condition of the material on the exterior\n- Foundation: Type of foundation\n- BsmtQual: Height of the basement\n- BsmtCond: General condition of the basement\n- BsmtExposure: Walkout or garden level basement walls\n- BsmtFinType1: Quality of basement finished area\n- BsmtFinSF1: Type 1 finished square feet\n- BsmtFinType2: Quality of second finished area (if present)\n- BsmtFinSF2: Type 2 finished square feet\n- BsmtUnfSF: Unfinished square feet of basement area\n- TotalBsmtSF: Total square feet of basement area\n- Heating: Type of heating\n- HeatingQC: Heating quality and condition\n- CentralAir: Central air conditioning\n- Electrical: Electrical system\n- 1stFlrSF: First Floor square feet\n- 2ndFlrSF: Second floor square feet\n- LowQualFinSF: Low quality finished square feet (all floors)\n- GrLivArea: Above grade (ground) living area square feet\n- BsmtFullBath: Basement full bathrooms\n- BsmtHalfBath: Basement half bathrooms\n- FullBath: Full bathrooms above grade\n- HalfBath: Half baths above grade\n- Bedroom: Number of bedrooms above basement level\n- Kitchen: Number of kitchens\n- KitchenQual: Kitchen quality\n- TotRmsAbvGrd: Total rooms above grade (does not include bathrooms)\n- Functional: Home functionality rating\n- Fireplaces: Number of fireplaces\n- FireplaceQu: Fireplace quality\n- GarageType: Garage location\n- GarageYrBlt: Year garage was built\n- GarageFinish: Interior finish of the garage\n- GarageCars: Size of garage in car capacity\n- GarageArea: Size of garage in square feet\n- GarageQual: Garage quality\n- GarageCond: Garage condition\n- PavedDrive: Paved driveway\n- WoodDeckSF: Wood deck area in square feet\n- OpenPorchSF: Open porch area in square feet\n- EnclosedPorch: Enclosed porch area in square feet\n- 3SsnPorch: Three season porch area in square feet\n- ScreenPorch: Screen porch area in square feet\n- PoolArea: Pool area in square feet\n- PoolQC: Pool quality\n- Fence: Fence quality\n- MiscFeature: Miscellaneous feature not covered in other categories\n- MiscVal: $Value of miscellaneous feature\n- MoSold: Month Sold\n- YrSold: Year Sold\n- SaleType: Type of sale\n- SaleCondition: Condition of sale",
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    {
      "name": "Description",
      "content": "This is the competition for day 3 of the course \"Introduction to Machine Learning\". \n\nThe competition dataset is the [Ames Housing Dataset](https://www.kaggle.com/prevek18/ames-housing-dataset). \n\nThe dataset has not been preprocessed by us. Try out feature extraction and preprocessing methods that have been covered today, and also try out dimensionality reduction using PCA. ",
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    {
      "name": "Evaluation",
      "content": "# Evaluation\nThe evaluation metric for this competition is Mean Absolute Error (MAE):\n$$\n\\frac{1}{n}\\sum_{i=1}^n |y^{(i)} - \\hat y^{(i)}|\n$$\n\n\nThe solution file should contain a header and have the following format:\n\n<pre>row_id,response<br />1,12000<br /><span style=\"font-size: 14px; line-height: 1.4em;\">2,8000<br />3,12500<br /><span style=\"font-size: 14px; line-height: 1.4em;\">4,6500<br /></span><span style=\"font-size: 14px; line-height: 1.4em;\">etc.</span>",
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