I have compared different regression technics for the diabete dataset
This a REGRESSION problem. Ten numeric predictive variables: age, sex, body mass index, average blood pressure, and six blood serum measurements. They were obtained for each of n = 442 diabetes patients, as well as the response of interest, a quantitative measure (integer between 25 and 346) of disease progression one year after baseline.
The goal is to predict as well as possible the future disease progression one year after (target value) as a function of the 10 predictive variables.
Note: Each of the 10 feature variables have been mean centered and scaled by the standard deviation times n_samples (i.e. the sum of squares of each column totals 1).