DCA algorithm for clusterwise linear regression and its comparison
Publish Year: 1396
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ICIORS10_089
تاریخ نمایه سازی: 11 شهریور 1397
Abstract:
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
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Authors
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