Logistic Regression
Logistic Regression is a statistical method used to analyze a dataset in which there are one or more independent variables that determine an outcome. It is used to model the probability of a certain class or event existing such as pass/fail, win/lose, alive/dead or healthy/sick. Logistic Regression is a type of Generalized Linear Model (GLM) that uses a logistic function to model a binary dependent variable. The logistic function, also called the sigmoid function, maps any input to a value between 0 and 1. This makes it suitable for modeling the probability of an event occurring as a function of other factors. Logistic Regression is widely used in various fields, including medical, social, and behavioral sciences, as well as in engineering and business.
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