Hierarchically penalized support vector machine with grouped variables

Bang, Sungwan; Kang, Jongkyeong; Jhun, Myoungshic; Kim, Eunkyung

doi:10.1007/s13042-016-0494-2

Cited by 12 publications

(1 citation statement)

References 18 publications

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“…In our future research, we will continue to solve the SUKP by developing EDAs and EAs such as the AAA, FWA, BSO, PSO and MFO and will find the best performing EAs. The other two research directions are (i) using more accurate discriminators to consolidate recent machine learning methods [40], and (ii) using adaptive frameworks to improve the robustness and accuracy.…”

Section: Discussionmentioning

confidence: 99%

Estimation of Distribution Algorithm Based on Lévy Flight for Solving the Set-Union Knapsack Problem

Liu

2019

IEEE Access

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This article investigates how to use the estimation of distribution algorithm based on Lévy flight to solve the set-union knapsack problem (SUKP). First, the mathematical model of the SUKP is introduced. Then, a quadratic greedy repair and optimization algorithm (Q-GROA), which deals with infeasible solutions, is proposed. Thereby, a new approach, the estimation of distribution algorithm based on Lévy flight (LFEDA) combined with the Q-GROA is also proposed to solve the SUKP. A number of experiments are performed on the SUKP datasets to evaluate the performance of our proposed model. The results verify that the proposed method is significantly better than other algorithms with respect to the solution's performance.INDEX TERMS Set-union knapsack problem, estimation of distribution algorithm, Lévy flight, repair and optimization.

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Section: Discussionmentioning

confidence: 99%