Nearest neighbor based pap smear cell classification using tabu search for feature selectionNearest neighbor based pap smear cell classification using tabu search for feature selection Πλήρης Δημοσίευση σε Συνέδριο Conference Full Paper 2015-11-062006en The problem of classification consists of using some known objects, usually described by a large vector of features, to induce a model that classifies others into known classes. Selecting the right set of features for classification is one of the most important problems in designing a good classifier. In this paper, a tabu search algorithm is proposed for the solution of the feature selection problem. Tabu Search is a well known and effective metaheuristic algorithm that was first introduced for the solution of combinatorial optimization problems. This algorithm is combined with a number of nearest neighbor based classifiers. The algorithm is tested in two sets of data for Pap-Smear Cell Classification. The first one consists of 917 images of Pap smear cells and the second set consists of 500 images, classified carefully by cyto-technicians and doctors. Each cell is described by 20 features, and the cells fall into 7 classes but a minimal requirement is to separate normal from abnormal cells, which is a 2 class problem.http://creativecommons.org/licenses/by/4.0/25-34 2nd European Symposium on Nature-inspired Smart Information Systems Marinakis Ioannis Μαρινακης Ιωαννης Dounias, G Pap smear Papanicolaou smear Papanicolaou test pap test pap smear papanicolaou smear papanicolaou test