A Method to Classify Shape Data using Multinomial Logistic Regression Model - Moghimbeygi, Meisam (Statistics, Optimization & Information Computing, 2025)
‎We introduced a multinomial logistic regression model to classify the labeled configurations‎. ‎In this modeling‎, ‎we use a power-divergence test to find an estimator for belonging probability in each category‎. ‎The estimator is introduced based on different distances‎. ‎Since the estimator is biased‎, ‎we modified the belonging probability by multinomial logistic regression‎. ‎We evaluate the performance of the proposed technique in the comprehensive simulation study‎. ‎Also‎, ‎we classified the five real data sets using our multinomial logistic model‎.