A Method to Classify Shape Data using Multinomial Logistic Regression Model
Abstract
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.
Published
2025-01-24
How to Cite
Moghimbeygi, M. (2025). A Method to Classify Shape Data using Multinomial Logistic Regression Model. Statistics, Optimization & Information Computing. https://doi.org/10.19139/soic-2310-5070-2215
Issue
Section
Research Articles
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