Housing Price Prediction

*Abount the Dataset:
Used in Belsley, Kuh & Welsch, 'Regression diagnostics …', Wiley,1980. N.B. Various transformations are used in the table on pages 244-261. Quinlan (1993). Combining Instance-Based and Model-Based Learning. In Proceedings on the Tenth International Conference of Machine Learning, 236-243, University of Massachusetts, Amherst. Morgan Kaufmann.

** Relevant Information: Concerns housing values in suburbs of Boston.
** Number of Instances: 509
** Number of Attributes: 13 continuous attributes (including "class" attribute "MEDV"), 1 binary-valued attribute.

Attribute Information:

1. CRIM : per capita crime rate by town.
2. ZN : proportion of residential land zoned for lots over 25,000 sq.ft.
3. INDUS: proportion of non-retail business acres per town.
4. CHAS : Charles River dummy variable (= 1 if tract bounds river; 0 otherwise).
5. NOX : nitric oxides concentration (parts per 10 million).
6. RM : average number of rooms per dwelling.
7. AGE : proportion of owner-occupied units built prior to 1940.
8. DIS : weighted distances to five Boston employment centres.
9. RAD : index of accessibility to radial highways.
10. TAX : full-value property-tax rate per $10,000.
11. PTRATIO : pupil-teacher ratio by town.
12. B : 1000(Bk - 0.63)^2 where Bk is the proportion of blacks by town.
13. LSTAT: % lower status of the population.
14. MEDV : Median value of owner-occupied homes in $1000's.*