DCA algorithm for clusterwise linear regression and its comparison
عنوان مقاله: DCA algorithm for clusterwise linear regression and its comparison
شناسه ملی مقاله: ICIORS10_089
منتشر شده در دهمین کنفرانس بین المللی انجمن تحقیق در عملیات ایران در سال 1396
شناسه ملی مقاله: ICIORS10_089
منتشر شده در دهمین کنفرانس بین المللی انجمن تحقیق در عملیات ایران در سال 1396
مشخصات نویسندگان مقاله:
Sona Taheri - Faculty of Science and Technology, Federation University Australia,Victoria, Australia
Adil M. Bagirov - Faculty of Science and Technology, Federation University Australia, Victoria, Australia
خلاصه مقاله:
Sona Taheri - Faculty of Science and Technology, Federation University Australia,Victoria, Australia
Adil M. Bagirov - Faculty of Science and Technology, Federation University Australia, Victoria, Australia
Clusterwise linear regression consists of finding a number of linear regression functions each approximating a subset of the data. It is a combination of two techniques: clustering and regression. We introduce an algorithm for solving the clusterwise linear regression problem using its nonsmooth optimization formulation and difference of convex representation. The algorithm is tested using real world data sets and compared with other clusterwise linear regression algorithms
کلمات کلیدی: Nonconvex optimization, DC optimization, Nonsmooth optimization, Clusterwise linear regression
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/766823/