Sciweavers

Share
ANOR
2010

Alternating local search based VNS for linear classification

10 years 1 months ago
Alternating local search based VNS for linear classification
We consider the linear classification method consisting of separating two sets of points in d-space by a hyperplane. We wish to determine the hyperplane which minimises the sum of distances from all misclassified points to the hyperplane. To this end two local descent methods are developed, one grid-based and one optimisation-theory based, and are embedded in several ways into a VNS metaheuristic scheme. Computational results show these approaches to be complementary, leading to a single hybrid VNS strategy which combines both approaches to exploit the strong points of each. Extensive computational tests show that the resulting method performs well. Keywords. Data Mining, Classification, Linear Classification, Heuristic Minimisation, Normdistance, Variable Neighbourhood Search, Variable Neighborhood Search, VNS, Local Search, Grid Search, Cell Search.
Frank Plastria, Steven De Bruyne, Emilio Carrizosa
Added 08 Dec 2010
Updated 08 Dec 2010
Type Journal
Year 2010
Where ANOR
Authors Frank Plastria, Steven De Bruyne, Emilio Carrizosa
Comments (0)
books