Building gradient descent (Linear Regression) from scratch with python - compared against scikit-learn
1. Project Overview:
(a) To work on multi-linear regression methodology of batch gradient descent without feature selection and regularization (penalty/weight-decay)
2. Dataset:
Boston Housing Data
3. Sources:
(a) Origin: This dataset was taken from the StatLib library which is maintained at Carnegie Mellon University.
(b) Creator: Harrison, D. and Rubinfeld, D.L. 'Hedonic prices and the demand for clean air', J. Environ. Economics & Management, vol.5, 81-102, 1978.
(c) Date: July 7, 1993
4. Number of Attributes:
13 continuous attributes (including "class" attribute "MEDV"), 1 binary-valued attribute.
5. Attribute Information:
| Index | Column | Description |
|---|---|---|
| 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 |