Ordin B.Uylaş N.2023-06-162023-06-1620109.79E+12https://hdl.handle.net/20.500.14365/397524th Mini EURO Conference on Continuous Optimization and Information-Based Technologies in the Financial Sector, MEC EurOPT 2010 -- 23 June 2010 through 26 June 2010 -- Izmir -- 106702In this paper we have proposed a semi-supervised algorithm based on quasisecant optimization method for solving data classification problems. The algorithm computes hyperplane(s) to separate two sets with respect to some tolerance. An error function is formulated and an algorithm for its minimization is expressed. We present results of numerical experiments using several UCI test data sets and compare the proposed algorithm with two supervised data classification algorithm (linear separability, max-min separability) and two support vector machine solvers (LIBSVM and SVM-light). © Izmir University of Economics, Turkey, 2010.eninfo:eu-repo/semantics/closedAccessNonsmooth optimizationQuasisecant methodSemi-supervised data classificationAlgorithmsOptimizationSupport vector machinesData classificationData classification problemsLinear separabilityNonsmooth optimizationNumerical experimentsOptimization methodQuasisecant methodSemi-supervised algorithmClassification (of information)Conference Object2-s2.0-84905454918