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Universitas Hasanuddin
Research output:Contribution to journal›Article›peer-review
Particle Swarm Optimization Algorithm to Determine Optimum Parameter of Least Square Support Vector Machine for Survival Analysis
Rahmawati
Aip Conference Proceedings
Published: 2026
Abstract
The Least Squares Support Vector Machine for Survival Analysis (Sur-LSSVM) determines the prognostic function as a hazard function in Cox regression. The PSO algorithm identifies the optimal regularization and kernel parameters that maximize the c-index. The data used is a breastfeeding dataset obtained from the Indonesia Family Life Survey. According to the model, the variables that significantly influence breastfeeding are health conditions and economic status with a c-index of 73.54%.
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10.1063/5.0318827Other files and links
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Particle swarm optimizationSciences
AlgorithmSciences
Computer scienceSciences
Support vector machineSciences
Mathematical optimizationSciences
MathematicsSciences
Survival analysisSciences
Optimization algorithmSciences
Multi-swarm optimizationSciences
Square (algebra)Sciences
Applied mathematicsSciences
Estimation theorySciences
Optimization problemSciences
Algorithm designSciences
Feature (linguistics)Sciences