Misclassification minimization

By Olvi L. Mangasarian. 1994

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Citations in the corpus

Supersparse linear integer models for optimized medical scoring systems (2015, background): “MIP formulations to minimize the 0–1 loss, for instance, were first proposed in Liittschwager and Wang (1978) and Bajgier and Hill (1982), and later refined by Mangasarian (1994), Asparoukhov and Stam (1997) and Glen (1999).”
Complementarity Formulations of ' 0 -norm Optimization Problems (2013, background): “The misclassification minimization problem that arises from the literature in support-vector machines [10, 30] provides an example of problem (2.”
Discrete support vector decision trees via tabu search (2004, background): “From one side, some papers (Mangasarian, 1994, 1996; Chunhui Chen and Mangasarian, 1996; La Torre and Vercellis, 2003) focused on the misclassi0cation rate alone, not in conjunction with the margin minimization, and transformed the discrete problem into a nonlinear optimization model by means of…”
Supervised classification and mathematical optimization (2013, background): “Other popular linear classifiers are the classical logistic regression (LR), [121], and the linear programming models proposed by Mangasarian in [158] [159].”
Mathematical Programming for Data Mining: Formulations and Challenges (1999, background): “LPECs can model machine learning problems [83, 86], while more general mathematical programs with equilibrium constraints (MPECs) [79] can model more general problems such as economic and traffic equilibrium problems.”
Bilevel Optimization and Machine Learning (2008, methodology): “The QP, (11), can be solved using the Frank-Wolfe method of [10] which simply involves solving a sequence of LPs until either a global minimum or some locally stationary solution of (6) is reached.”
Oblique Multicategory Decision Trees Using Nonlinear Programming (2005, methodology): “Typically, these systems minimize some measure of the distance of the misclassified points from the separating plane, although more recent techniques (Mangasarian 1994, Chen and Mangasarian 1996, Bennett and Bredensteiner 1997) directly minimize the number of such points.”