Logistic Regression: Notes and Interview Questions
What is Logistic Regression? It’s a classification algorithm, that is used where the response variable is categorical. The idea of Logistic Regression is to find a relationship between features and the probability of a particular outcome. Binomial Logistic Regression - response variable has two values 0 and 1 or pass and fail. Multinomial Logistic Regression - response variable can have three or more possible values. The idea of Logistic Regression. f(z) = 1/(1+e -z ) The values of Z will vary from -infinity to +infinity. The values of a logistic function will range from 0 to 1. Logistic regression can convert the values of logits (logodds), which can range from -infinity to +infinity to a range between 0 and 1. What are the assumptions of Logistic Regression? Linear Relation between independent features and the log odds (logit of the outcome). No multicollinearity among predictors. Observations to be independent of each other. Advantages Logistic Regression Are very ea...