Optimizing SVR using Local Best PSO for Software Effort Estimation
Abstract: In the software
industry world, it’s known to fulfill the tremendous demand. Therefore,
estimating effort is needed to optimize the accuracy of the results, because it
has the weakness in the personal analysis of experts who tend to be less
objective. SVR is one of clever algorithm as machine learning methods that can
be used. There are two problems when applying it; select features and find
optimal parameter value. This paper proposed local best PSO-SVR to solve the
problem. The result of experiment showed that the proposed model outperforms
PSO-SVR and T-SVR in accuracy.
Keywords: Optimization, SVR,
Optimal Parameter, Feature Selection, Local Best PSO, Software Effort
Estimation
Author: Dinda Novitasari, Imam
Cholissodin, Wayan Firdaus Mahmudy
Journal Code: jptinformatikagg160008
