Machine learning project where I used various dimension reduction/feature selection machine learning models such as ridge regression and lasso regression, as well as best subset selection and forward selection, in order to predict Boston housing prices.
housing.csv concerns housing values in suburbs of Boston. The dataset was created by Harrison, D. and Rubinfeld, D.L. and analyzed in 'Hedonic prices and the demand for clean air', J. Environment Economics and Management, vol. 5, 81 - 102, 1978. There are 506 observaitons and 12 continuous attributes including the response variable MEDV.