Hsieh, S.-H.S.-H.HsiehWang, Z.Z.WangCheng, P.-H.P.-H.ChengLee, I.-S.I.-S.LeeHsieh, S.-L.S.-L.HsiehFEI-PEI LAI2020-04-162020-04-162010https://scholars.lib.ntu.edu.tw/handle/123456789/484433In the paper, we classify cancer with the Leukemia cancer of medical diagnostic data. Information gain has been adapted for feature selections. A Leukemia cnacer model that utilizes Information Gain based on Support Vector Machines (IG-SVM) techniques and enhancements to evaluate, interpret the cacer classification. The experimental results indicate that the SVM model illustrates the highest accuracy of classifications for Leukemia cancer. ? 2010 IEEE.Leukemia cancer; Microarray; Support vector machine[SDGs]SDG3Cancer classification; Feature selection; Information gain; Leukemia cancer; Medical diagnostics; SVM model; Diseases; Gears; Information science; Vectors; Support vector machinesconference paper10.1109/INDIN.2010.55496382-s2.0-77956563893https://www.scopus.com/inward/record.uri?eid=2-s2.0-77956563893&doi=10.1109%2fINDIN.2010.5549638&partnerID=40&md5=288a6756c8c0e7571d9bb40d314bdb3b