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Feature Subset Selection for Ordered Logit Model via Tangent-Plane-Based Approximation
2019
IEICE transactions on information and systems
This paper is concerned with a mixed-integer optimization (MIO) approach to selecting a subset of relevant features from among many candidates. For ordinal classification, a sequential logit model and an ordered logit model are often employed. For feature subset selection in the sequential logit model, Sato et al. [22] recently proposed a mixed-integer linear optimization (MILO) formulation. In their MILO formulation, a univariate nonlinear function contained in the sequential logit model was
doi:10.1587/transinf.2018edp7188
fatcat:nkzsognurfb7ljnulrfycvlnku