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2025-06-02 10:12:42

This https://arxiv.org/abs/2401.03276 has been replaced.
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Robust Binary and Multinomial Logit Models for Classification with Data Uncertainties
Binary logit (BNL) and multinomial logit (MNL) models are the two most widely used discrete choice models for travel behavior modeling and prediction. However, in many scenarios, the collected data for those models are subject to measurement errors. Previous studies on measurement errors mostly focus on "better estimating model parameters" with training data. In this study, we focus on using BNL and MNL for classification problems, that is, to ``better predict the behavior of new samples'' when…