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Nearest neighbor based pap-smear cell classification using tabu searchfor feature selection

Marinakis Ioannis, George Dounias

Απλή Εγγραφή

URIhttp://purl.tuc.gr/dl/dias/F56224F2-B5D8-460C-891E-9746A5A0BC09-
Γλώσσαen-
ΤίτλοςNearest neighbor based pap-smear cell classification using tabu search for feature selectionen
ΔημιουργόςMarinakis Ioannisen
ΔημιουργόςΜαρινακης Ιωαννηςel
ΔημιουργόςGeorge Douniasen
ΠερίληψηThe 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.en
ΤύποςΠερίληψη Δημοσίευσης σε Συνέδριοel
ΤύποςConference Paper Abstracten
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2015-10-30-
Ημερομηνία Δημοσίευσης2006-
Βιβλιογραφική ΑναφοράY. Marinakis and G. Dounias, (2006), “Nearest Neighbor Based Pap Smear Cell Classification Using Tabu Search for Feature Selection”, presented at The Pap Smear Benchmark, Intelligent and Nature Inspired Approaches in Pap Smear Diagnosis, Special Session Proceedings of the NISIS - 2006 Symposium, Tenerife, Spain, 2006.en

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