Logistic Regression, Generalized Linear Model, Machine Learning, Data Science, Statistical Learning.
following The explanatory variables (X) are assumed to be given, so we model expected response y given X. Why do we model expected value? Since, we assume the actual response to be a noisy version of actual underlying response where the error/noise can not be modeled. In Logistic Regression the