Understanding Logistic Regression Analysis. Introduction to Computational Data Analysis CX4240 Lecture 09 Logistic Regression Chao. The procedure is quite similar to multiple linear regression with the exception that the response variable is binomial.
Logistic Regression is a popular statistical model used for binary classification that is for predictions of the type this or that yes or no A or B etc. It is named as Logistic Regression because its underlying technique is quite the same as Linear Regression. Applied Logistic Regression Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software.
Logistic regression can however be used for multiclass classification but here we will focus on its simplest application.
In a classification problem the target variable or output y can take only discrete values for given set of features or inputs X. The result is the impact of each variable on the odds ratio of the observed event of interest. The procedure is quite similar to multiple linear regression with the exception that the response variable is binomial. May 17 2018 Logistic Regression is one of the basic and popular algorithm to solve a classification problem.
