Title :
Binary Classification Based on Potentials
Author :
Boczko, Erik M. ; Di Lullo, A. ; Young, Todd R.
Author_Institution :
Biomed. Inf., Vanderbilt Univeristy Med. Center, Nashville, TN, USA
Abstract :
We introduce a simple and computationally trivial method for binary classification based on the evaluation of potential functions. We demonstrate that despite the conceptual and computational simplicity of the method its performance can match or exceed that of standard Support Vector Machine methods.
Keywords :
bioinformatics; learning (artificial intelligence); medical computing; radial basis function networks; binary classification; distance weighted discrimination; machine learning; potential functions; radial basis function networks; Bioinformatics; Biomedical computing; Biomedical informatics; Collaboration; Joining processes; Machine learning; Mathematics; Proteomics; Support vector machine classification; Support vector machines; Machine Learning; Microarray Data;
Conference_Titel :
Bioinformatics, 2009. OCCBIO '09. Ohio Collaborative Conference on
Conference_Location :
Cleveland, OH
Print_ISBN :
978-0-7695-3685-9
DOI :
10.1109/OCCBIO.2009.31
