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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Shahbudin, S. Hussain, A. Samad, S.A. Tahir, N.M. |
| Copyright Year | 2008 |
| Description | Author affiliation: Electron.&Syst. Eng. Dept., Nat. Univ. of Malaysia, Bangi (Shahbudin, S.; Hussain, A.; Samad, S.A.) || Fac. of Electr. Eng., Technol. Univ. of Mara, Shah Alam (Tahir, N.M.) |
| Abstract | Maximizing the classification performance of the training data is a typical procedure in training a classifier. It is well known that training a Support Vector Machine (SVM) requires the solution of an enormous quadratic programming (QP) optimization problem. Serious challenges appeared in the training dilemma due to immense training and this could be solved using Sequential Minimal Optimization (SMO). This paper investigates the performance of SMO solver in term of CPU time, number of support vector and decision boundaries when applied in a 2-dimensional datasets. Next, the chunking algorithm is employed for comparison purpose. Initial results demonstrated that the SMO algorithm could enhance the performance of the training dataset. Both algorithms illustrated similar patterns from the decision boundaries attained. Classification rate achieved by both solvers are superb. |
| Starting Page | 373 |
| Ending Page | 378 |
| File Size | 296932 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424423835 |
| ISSN | 1062922X |
| DOI | 10.1109/ICSMC.2008.4811304 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-10-12 |
| Publisher Place | Singapore |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Support vector machines Support vector machine classification Quadratic programming Kernel Performance analysis Data engineering Optimization methods Data visualization Algorithm design and analysis Testing support vector machine Sequential Minimal Optimization Chunking algorithm decision boundaries |
| Content Type | Text |
| Resource Type | Article |
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