Logistic regression is a statistical model that is used to analyze the relationship between a binary dependent variable and one or more independent variables. It is a popular machine learning algorithm that is widely used in various applications such as credit scoring, fraud detection, and medical research. In this article, we will discuss the key aspects of logistic regression, including its definition, assumptions, implementation, and evaluation. Definition Logistic regression is a type of regression analysis that is used when the dependent variable is binary (i.e., only two possible values). The objective of logistic regression is to find the best-fit equation that describes the relationship between the independent variables and the probability of the dependent variable taking a specific value. The resulting equation can be used to predict the probability of the dependent variable based on the values of the independent variables. The logistic regression equation is expressed ...