I am building a model to predict probabilities based on the scores given by a logistic regression. I have tried cv.glmnet but it doesn't give the probability score, instead it gives scores lying in (-0.06,0.289).
Please suggest a modeling technique that would predict probabilities which uses probabilities from another model as a DV.
Note: I used the same input for glm.fit function and it gives predicted probabilities ranging from 0 to 1 even when the dv is supposed to be binary when the family is assigned as binomial(). I believe the result is error prone as it is not designed to do it. It would be helpful if someone can explain this anomaly.