Methods and Models for Interpretable Linear Classification

16 May 2014 Berk Ustun Cynthia Rudin

We present an integer programming framework to build accurate and interpretable discrete linear classification models. Unlike existing approaches, our framework is designed to provide practitioners with the control and flexibility they need to tailor accurate and interpretable models for a domain of choice... (read more)

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