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This document provides an overview of classification methods in statistics, focusing on logistic regression and its applications for predicting binary outcomes, such as credit card defaults. It discusses the limitations of regression methods for qualitative responses, introduces multinomial logistic regression for multi-class classification, and covers probit and Poisson regression for binary and count data, respectively. The document emphasizes the use of maximum likelihood estimation for model fitting and

Author

Niyati Shah

Language

EN