The Logistic regression is a linear model used for binomial regression. It is used in medical science and to predict a customer’s tendency to purchase a product. It makes use of predictor variables for this purpose.
Logistic Regression allows easier analysis of results in the form of odds ratios and statistical hypothesis testing.
A generalized linear model has taken input for a non-linear link function. The linear model has the following form −
z = c1x1 + c2x2 + … cnxn + i = ct x + i
c is the coefficient vector, i is the intercept value x is the observation vector