For example, if I have a sample with a decision score of -6 and another with a score of -3, which sample is closer to the hyperplane?
Also, does the probability of a sample belonging to a class increase with its respective distance from the hyperplane (larger distance from hyperplane = larger probability)?
I am using sklearn's decision_function
and predict_proba
functions to get these values if it makes a difference.
Thanks.