MIXED-INTEGER SUPPORT VECTOR MACHINE

How researchers see this paper

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Learning Optimized Risk Scores (2016, background): “Our work is part of a recent stream of research on integer programming in supervised learning (Carrizosa et al., 2016; Liu and Wu, 2007; Goldberg and Eckstein, 2012; Guan et al., 2009; Nguyen and Franke, 2012; Sato et al., 2015, 2016; Bertsimas et al., 2016; Bertsimas and Dunn, 2017).”
Supersparse linear integer models for optimized medical scoring systems (2015, methodology): “Since the adult and haberman datasets were imbalanced, we trained all methods on these datasets with a weighted loss function where we set W+ = N−/N and W− = N+/N .”
Methods and Models for Interpretable Linear Classification (2014, methodology): “Recent progress in commercial MIP software has made it possible to solve exponentially larger problems [13, 12], and ushered in new MIP classification models that involve feature selection [42, 45, 46, 84], or the creation of a reserved-judgement region [22, 21].”