April 2019
Beginner to intermediate
1240 pages
45h 43m
English
Content preview from Data Science for Business and Decision Making
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Chapter 14
Binary and Multinomial Logistic Regression Models
Abstract
This chapter presents the binary and multinomial logistic regression models, establishing the circumstances based upon which the binary and multinomial regression models can be used. The objective is to estimate an occurrence probability model of an event based on the maximum likelihood method. The results of statistics tests pertinent to the logistic models are evaluated. Confidence intervals of the model parameters for the purpose of prediction are also elaborated, as well as the analysis of sensitivity and interpretation of the sensitivity curve, the ROC curve and the cutoff concepts, overall model efficiency, sensitivity, and specificity. The binary and multinomial regression ...
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