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Boston Housing dataset contains aggregated data on various features for houses in Greater Boston communities, including the median value of home for each of those areas. An optimal model based on a statistical analysis is developed first. Then the model is used to estimate the best selling price for a home.

DecisionTreeRegressor and GridSearchCV from sklearn are used.

To run the program:
python boston_housing.py

The dataset used in this project is included with the scikit-learn library (sklearn.datasets.load_boston). You do not have to download it separately. You can find more information on this dataset from the UCI Machine Learning Repository page.