TY - JOUR T1 - K-Ortalama Kümelerinin Sınıf Bilgisi Olarak Karar Ağacı Oluşturmada Kullanılması ve Glokom Çoklu Sınıflandırılmasında Başarıma Etkisi TT - Usage Of K-Means Clusters as Class Labes In Decısıon Trees and Its Effect On Multıclassıfıcatıon Performance Of Glaucoma AU - Yücebaş, Sait Can AU - Kınacı, Ahmet Cumhur PY - 2016 DA - March JF - Duzce University Journal of Science and Technology JO - DUBİTED PB - Düzce Üniversitesi WT - DergiPark SN - 2148-2446 SP - 747 EP - 755 VL - 4 IS - 2 LA - tr AB - Bu çalışma çoklu sınıflandırmada performans artırımı için K-Ortalama ve Karar Ağacı yöntemlerinden oluşan bir model sunmaktadır. Model glukom veri kümesi üzerinde test edilmiş kesinlik ölçütü 0,808, ROC alanı 0,839 bulunmuştur. KW - Veri Madencliği KW - Sınıflama KW - Kümeleme KW - K-Ortalama KW - Karar Ağacı N2 - In this study a model of K-Means - Decision Tree is presented to increase the multiclassification performance. This model is tested on glaucoma dataset, the accuracy and the are under ROC curve is calculated as 0.808, 0.839 respectively. CR - E.S. Berner, Clinical Decision Support Systems: State of the Art. AHRQ Publication, Rockville, MD (2009). CR - E. Coiera, Clinical Decision Support Systems: Guide to Health Informatics. 3rd Edition, CRC CR - Press, (2003) CR - Sen, Arun et al. Journal of Biomedical Informatics 45(5)(2012)1009–1017. CR - A. Satyanandam et al. International Journal of Computer & Organization CR - Trends.2(3)(2012)53-60 CR - I. Kononenko Artificial Intelligence in Medicine 23(1)(2001)89–109 CR - M. You et al. Int J Data Min Bioinform. 5(4)(2011)383-401. CR - N. Mehra, S. Grupta International Journal of Computer Science and Information CR - Technologies 4(4)(2013)572 – 576 CR - G. Tsoumakas, I. Katakis Data Warehousing and Mining: Concepts, Methodologies, Tools, CR - and Applications,6. Baskı, IGI Global, (2008) CR - B.M. Shahshahani, D.A. Landgrebe. Geoscience and Remote Sensing 32(5)(1994)1087 – 1095 CR - S.W. Kim, R.P.W. Duin, On Improving Dissimilarity-Based Classifications Using a Statistical Similarity Measure, 15th Iberoamerican Congress on Pattern Recognition, Sao Paulo – Brazil, CR - (2010) 418–425 CR - Savini et al. Current Opinion in Ophthalmology 22 (2)(2011)115–123 CR - Y. Burnstein et al. American Journal of Ophthalmology 129(3)(2000)328–333 CR - L. Churilov et al. Journal of Management Information Systems 21(4)(2005)85-100 CR - X. Wu et al. Knowl. Inf. Syst. 14(1)(2008):1-37 CR - M. Bramer, Principles of data mining, 1st Ed., Springer-Verlag, (2007) CR - Anonim, CR - http://www.academia.edu/4857097/Integrating_Clustering_with_Different_Data_Mining_Techniques_in_the_Diagnosis_of_Heart_Disease (Erişim tarihi: 17th of January, 2015) CR - N.S. Nithya et al. International Journal of Computer Science Trends and Technology CR - (2)(2013)17-23 CR - P. Filipczuk et al. Image Processing and Communications Challenges, 3. Baskı, Springer, CR - (2011) CR - U. Orhan et al. Expert Systems with Applications 38(10)(2011)13475–13481. CR - J. Demsar et al. Journal of Machine Learning Research 14(2013)2349-2353. CR - P. Rousseeuw et al. Journal of Statistical Software 1(4)(1996)1-30. CR - A.T. Azar et al. Neural Computing and Applications 23(7)(2013)2387-2403. CR - J.C. Mwanza et al. Ophthalmology 119(6)(2012)1151–1158. CR - O. Tan et al. Ophthalmology 116(12)(2009)2305–2314. CR - R. Sihota et al. Invest Ophthalmol Vis Sci 47(5)(2006)2006-2010. CR - Z. Yang et al. PLoS ONE 10(5)(2015)e0125957. CR - C. Bowd, M.H.Goldbaum Optometry & Vision Science 85(6)(2008) 396–405. UR - http://dergipark.org.tr/tr/pub/dubited/issue//258422 L1 - http://dergipark.org.tr/tr/download/article-file/224844 ER -