Fusion of stability and multi-objective optimization for solving cancer tissue classification problem
作者：
Highlights：
• A multiobjective clustering technique using the concepts of stability is proposed.
• The hypothesis is that small perturbations cannot destroy the optimal structure.
• Proposed algorithm is not depended on the number of perturbed datasets used.
• Results are shown for cancer tissue sample classification.
• Biological and statistical significance tests are also conducted.
摘要
•A multiobjective clustering technique using the concepts of stability is proposed.•The hypothesis is that small perturbations cannot destroy the optimal structure.•Proposed algorithm is not depended on the number of perturbed datasets used.•Results are shown for cancer tissue sample classification.•Biological and statistical significance tests are also conducted.
论文关键词：Multi-objective optimization,Stability,Simulated annealing,Cancer-tissue sample classification
论文评审过程：Received 11 September 2017, Revised 31 May 2018, Accepted 25 June 2018, Available online 12 July 2018, Version of Record 20 July 2018.
论文官网地址：https://doi.org/10.1016/j.eswa.2018.06.059
