Classification Thyroid Disease Using Multinomial Logistic Regressions (LR)

Abstract

Classifying using Multinomial Logistic Regression is one of the techniques used in the statistical model. Binomial logistic regression is a form of regression that is used when the dependent is a dichotomy and the independents are continuous variables, categorical variables, or both. Multinomial Logistic Regression Model is used to handle the case of dependent variables with more classes and suitable for non-linear data by using Maximum Likelihood Estimation and Wald Statistics. This experiment aims to predict the Thyroid disease Dataset by using the Multinomial Logistic Regression model. In this experiment, SPSS software is used to run the Multinomial Logistic Regression by Thyroid disease data supplied by Randolf Werner, which was adopted from the UCI Repository of Machine Learning Database.