LOGISTIC REGRESSION
INTRODUCTION: It is a statistic method that is used for building machine learning models where the dependent variable is binary. It is used to describe data and the relationship between one dependent variable and one or more independent variables. The name "logistic regression" is derived from the concept of the logistic function that is uses. The logistic function is also known as the sigmoid function. The value of this logistic function lies between zero(0) and one(1). It is Supervised Classification Algorithm. The value of the logistic regression must be between 0 and 1, which cannot go beyond this limit, so it forms a curve like the "S" form. The S-form curve is called the Sigmoid function or the logistic function. LOGISTIC REGRESSION EQUATION: The Logistic regression equation can be obtained from the Linear Regression equation. The mathematical steps to get Logistic Regression equations are given below: The equation of the straight line can be written as: ...
