Generalized Linear Models (GLMs) extend the ordinary Linear Regression and allow the response variable y to have an error distribution other than the normal
This post is part of a series covering the exercises from Andrew Ng's machine learning class on Coursera. The original code, exercise text, and data files for this post are available here. Part 1 - Simple Linear Regression Part 2 - Multivariate Linear Regression Part 3 - Logistic Regression Part
The Logistic Regression Model - I have shared R Code for Logistic regression - whereas Logistic regression has the classic , Classification advantage , where the "Credit Seeker" can be marked as "Good"