Fit a logistic probability model based on Lasso penalty
Lasso(xvec,y,xnew,lambda)An input matrix. Each row is a vectorized predictor.
Binary response variable.
New predictors in the test data. Organized as a matrix with each row being a data point.
The regularization penalty.
The returned object is a list of components.
B_est - The estimated coefficient vector of linear predictor.
prob - The predicted probabilities for the test data.