The feature subset selection, along with the parameters of classifier significantly influences the classification accuracy. In order to ensure the optimal classification performance, the artificial bee colony (ABC) algorithm is proposed to simultaneously optimize the feature subset and the parameters of support vector machines (SVM), meanwhile for improving the optimizing performance of ABC algorithm, the initialization and scout bee phase are improved. To evaluate the proposed approach, the simulation was executed based on datasets from the UCI database. The effectiveness of the proposed method is confirmed by simulation results.
|Title of host publication||Conference Proceedings - 2016 International Conference on Advanced Mechatronic Systems, ICAMechS 2016|
|Number of pages||6|
|Publication status||Published - 16 Jan 2017|
|Event||2016 International Conference on Advanced Mechatronic Systems, ICAMechS 2016 - Melbourne, Australia|
Duration: 30 Nov 2016 → 3 Dec 2016
|Conference||2016 International Conference on Advanced Mechatronic Systems, ICAMechS 2016|
|Period||30/11/16 → 3/12/16|