Logistic Regression— Machine Learning Algorithms with Implementation in Python



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What is Logistic Regression?

Logistic Regression is a variation of Linear Regression and is used for classification purposes. The classification is based on the concept of probability

Logistic Regression makes use of a cost function named “Sigmoid function” which basically transforms any real value into a value between 0 and 1. The equation of Sigmoid function is as follows:

Sigmoid Function Equation

This results in the following graph:

Graph for Sigmoid Function

For classification, we define a threshold. For instance, any output value from the sigmoid function above 0.5 will be classified as class 1, and any value below or equal to 0.5 will be classified as class 0. We can do the same for multiple classes as well.

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