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    A distributionally robust machine learning model of simultaneous classification and feature selection under data uncertainty: Theory, methods, and application to the identification of Alzheimer's disease using handwriting

    A distributionally robust machine learning model of simultaneous classification and feature selection under data uncertainty: Theory, methods, and application to the identification... by Q.Y. Huang, N.D. Dizon, N. Jeyakumar, V. Jeyakumar

    Published 2025-01-01

    In this paper, we introduce an efficient machine learning method based on robust Support Vector Machines (SVMs) that simultaneously classifies data and selects relevant features whilst accounting for data uncertainty. Based on Wasserstein distributionally robust optimization, we develop computationa...

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