title: Using Lasso for non-linear regression (Python)
body: <p>I have a set of independent data points X, and a set of dependent points Y, and I would like to find a model of the form:</p>
  
  <p>(a<sub>0</sub>+a<sub>1</sub>*x<sub>1</sub>+a<sub>2</sub>*x<sub>2</sub>+...+a<sub>m</sub><em>x<sub>m</sub>)</em>(a<sub>m+1</sub>*x<sub>m+1</sub>+a<sub>m+2</sub>*x<sub>m+2</sub>)</p>
  
  <p>I know I can use scipy's curve_fit, but to avoid overfitting, I want to use Lasso for the linear part (i.e. the part in the first set of parenthesis).</p>
  
  <p>Is there a simple way of doing that in Python?</p>