Logistic Regression

Think of a question "Will it rain today evening?". To answer the question, various inputs need to be considered: temperature, humidity, wind etc. And the answer will be either "It is very likely" or "It is not likely. If you think of the process, and the outcome, the influence of various independent variables was considered and the probability of a discrete outcome was given. The model will not deliver an absolute answer but rather given you the probability of one of the discrete outcome happening.

The function used to determine the probability of the outcome is a called a logit function. So Logistic regression is also known as logit regression. The output of a logit function lies between 0 and 1 (probability).

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