House Prices

House Prices

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Description

Ask a home buyer to describe their dream house, and they probably won’t begin with the height of the basement ceiling or the proximity to an east-west railroad. But this competition’s dataset proves that much more influences price negotiations than the number of bedrooms or a white-picket fence. Predict sales prices and practice feature engineering using regression methods of your choice.

Goal

It is your job to predict the sales price for each house. For each Id in the test set, you must predict the value of the SalePrice variable.

Metric

Submissions are evaluated on Root-Mean-Squared-Error (RMSE) between the logarithm of the predicted value and the logarithm of the observed sales price. (Taking logs means that errors in predicting expensive houses and cheap houses will affect the result equally.)

Submission File Format

The file should contain a header and have the following format:

Id,SalePrice 1461,169000.1 1462,187724.1233 1463,175221 etc.

You can download an example submission file (sample_submission.csv) on the Data page.