- The logistic regression assumes that there is minimal or no multicollinearity among the independent variables.
- The Logistic regression assumes that the independent variables are linearly related to the log of odds.
- The logistic regression usually requires a large sample size to predict properly.
- The Logistic regression which has two classes assumes that the dependent variable is binary and ordered logistic regression requires the dependent variable to be ordered, for example Too Little, About Right, Too Much.
- The Logistic regression assumes the observations to be independent of each other.
Written by Dhiraj K
Data Scientist & Machine Learning Evangelist. I like to mess with data. dhiraj10099@gmail.com