This paper proposes two methods which take advantage of k -mean clustering algorithm to decrease the number of support vectors (SVs) for the training of support vector machine (SVM...
Xiao-Lei Xia, Michael R. Lyu, Tat-Ming Lok, Guang-...
In this paper, we investigate an approach based on support vector machines (SVMs) for detection of microcalcification (MC) clusters in digital mammograms, and propose a successive ...
Issam El-Naqa, Yongyi Yang, Miles N. Wernick, Niko...
Experimental results of texture features derived from Gabor and other four wavelet transforms classified and clustered based on Support Vector Machine (SVMs) and Self-Organizing M...
In this paper we apply three pattern recognition methods (support vector machine, cluster analysis and principal component analysis) to distinguish regulatory regions from coding a...
Rene te Boekhorst, Irina I. Abnizova, Lorenz Werni...
Background: Recent progress in cDNA and EST sequencing is yielding a deluge of sequence data. Like database search results and proteome databases, this data gives rise to inferred...
Michael Spitzer, Stefan Lorkowski, Paul Cullen, Al...