TY - JOUR ID - 10378 TI - Using multiple classifier system for diagnosis of endometriosis: an ensemble subspace approach JO - Journal of Advanced Mathematical Modeling JA - JAMM LA - en SN - 2251-8088 AU - Akhoond, Mohammad Reza AU - Bagheri, Mohammad Ali AU - Mousavi, Ali AU - Moini, Ashraf AD - Department of Statistics, Shahid Chamran University, Ahvaz, Iran AD - Department of Industrial Engineering, Tarbiat Modares University, Tehran, Iran AD - 2Department of Industrial Engineering, Tarbiat Modares University, Tehran, Iran AD - Department of Endocrinology and Female Infertility, Royan Institute for Reproductive Biomedicine, ACECR, Tehran, Iran Y1 - 2015 PY - 2015 VL - 2 IS - 2 SP - 89 EP - 107 KW - Prediction KW - Multiple classifier systems KW - Endometriosis diagnosis KW - Random subspace approach DO - N2 - One efficient approach in classification is using a set of individual classifiers and then combining their outputs, usually knows as ensemble classification or multiple classifier system. In this paper, an ensemble classification system based on the random subspace approach is employed for diagnosis of endometriosis, in which individual classifiers of the ensemble system are trained with different feature subsets. Finally, for classifying an unknown test sample, classifiers’ outputs are fused using the majority voting combination rule. UR - https://jamm.scu.ac.ir/article_10378.html L1 - ER -