Cargando…

SVM Classifier – a comprehensive java interface for support vector machine classification of microarray data

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 perfor...

Descripción completa

Detalles Bibliográficos
Autores principales: Pirooznia, Mehdi, Deng, Youping
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1780131/
https://www.ncbi.nlm.nih.gov/pubmed/17217518
http://dx.doi.org/10.1186/1471-2105-7-S4-S25
_version_ 1782131852121735168
author Pirooznia, Mehdi
Deng, Youping
author_facet Pirooznia, Mehdi
Deng, Youping
author_sort Pirooznia, Mehdi
collection PubMed
description 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 .
format Text
id pubmed-1780131
institution National Center for Biotechnology Information
language English
publishDate 2006
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-17801312007-01-24 SVM Classifier – a comprehensive java interface for support vector machine classification of microarray data Pirooznia, Mehdi Deng, Youping BMC Bioinformatics Research 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 . BioMed Central 2006-12-12 /pmc/articles/PMC1780131/ /pubmed/17217518 http://dx.doi.org/10.1186/1471-2105-7-S4-S25 Text en Copyright © 2006 Pirooznia and Deng; licensee BioMed Central Ltd http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Pirooznia, Mehdi
Deng, Youping
SVM Classifier – a comprehensive java interface for support vector machine classification of microarray data
title SVM Classifier – a comprehensive java interface for support vector machine classification of microarray data
title_full SVM Classifier – a comprehensive java interface for support vector machine classification of microarray data
title_fullStr SVM Classifier – a comprehensive java interface for support vector machine classification of microarray data
title_full_unstemmed SVM Classifier – a comprehensive java interface for support vector machine classification of microarray data
title_short SVM Classifier – a comprehensive java interface for support vector machine classification of microarray data
title_sort svm classifier – a comprehensive java interface for support vector machine classification of microarray data
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1780131/
https://www.ncbi.nlm.nih.gov/pubmed/17217518
http://dx.doi.org/10.1186/1471-2105-7-S4-S25
work_keys_str_mv AT piroozniamehdi svmclassifieracomprehensivejavainterfaceforsupportvectormachineclassificationofmicroarraydata
AT dengyouping svmclassifieracomprehensivejavainterfaceforsupportvectormachineclassificationofmicroarraydata