Document Type
Article
Publication Date
12-12-2006
Department
Biological Sciences
School
Biological, Environmental, and Earth Sciences
Abstract
Motivation
Graphical user interface (GUI) software promotes novelty by allowing users to extend the functionality. SVM Classifier is a cross-platform graphical application that handles very large datasets well. The purpose of this study is to create a GUI application that allows SVM users to perform SVM training, classification and prediction.
Results
The GUI provides user-friendly access to state-of-the-art SVM methods embodied in the LIBSVM implementation of Support Vector Machine. We implemented the java interface using standard swing libraries.
We used a sample data from a breast cancer study for testing classification accuracy. We achieved 100% accuracy in classification among the BRCA1–BRCA2 samples with RBF kernel of SVM.
Conclusion
We have developed a java GUI application that allows SVM users to perform SVM training, classification and prediction. We have demonstrated that support vector machines can accurately classify genes into functional categories based upon expression data from DNA microarray hybridization experiments. Among the different kernel functions that we examined, the SVM that uses a radial basis kernel function provides the best performance.
The SVM Classifier is available at http://mfgn.usm.edu/ebl/svm/
Publication Title
BMC Bioinformatics
Volume
7
Issue
S4
First Page
1
Last Page
7
Recommended Citation
Pirooznia, M.,
Deng, Y.
(2006). SVM Classifier: A Comprehensive Java Interface for Support Vector Machine Classification of Microarray Data. BMC Bioinformatics, 7(S4), 1-7.
Available at: https://aquila.usm.edu/fac_pubs/8567
Comments
Published by BMC Bioinformatics at 10.1186/1471-2105-7-S4-S25.