Support Vector Machines for Classification

S. R. Gunn, Support Vector Machines for Classification and Regression, Technical Report, Faculty of Engineering, Science and Mathematics, School of Electronics and Computer Science, University of Southampton, May 1998. 

Brereton RG, Lloyd GR. Support vector machines for classification and regression. Analyst 2010 135 230. 

Trotter, M.W. B., Holden, S.B. (2003) Support vector machines for ADME property classification. QSAR e[ Combinatorial Sci. 22, 533-548. 

Land W. H., Jr., Leibensperger D., Wong L., Sadik O., Wanekaya A., Uematsu M., and Embrechts M. J., New results using multi array sensors and support vector machines for the detection and classification of organophosphate nerve agents, in Systems, Man and Cybernetics, IEEE International Conference, October, pp. 2883-2888, 2003. 

Abe, S. (2005). Support vector machines for pattern classification. Springer, ISBN 1852339299, London, UK... 

Statnikov A, Wang L, Aliferis CF (2008) A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification. BMC bioinforma 9 319... 

Jerebko AK, Malley JD, Eranaszek M et al (2005) Support vector machines committee classification method for computer-aided polyp detection in CT coionography. Acad Radiol 12 479-486... 

Huang, C., Davis, L.S., Townshend, J.R.G., 2002. An assessment of support vector machines for land cover classification. Int. J. Remote Sens. 23, 725-749. 

Sugumaran, V, Muralidharan, V. Ramachandran, K.L 2007. Feature selection using decision tree and classification through proximal support vector machine for fault diagnostics of roller bearing. Mechanical Systems and Signal Processing 21(2) 930—942. 

The v-support vector machine for both classification and regression problems introduced by Scholkopf et al. [121] attempt to overcome the above mentioned disadvantages of C-SVM. The formulation of v-SVM removes the constant C, and introduces a new parameter v. As a primal problem for v-SVM, the following optimization problem is considered ... 

We illustrate the application of support vector machines for aroma classification using as our example 98 tetra-substituted pyrazines (Figure 52) representing three odor classes, namely 32 green, 23 nutty, and 43 bell-pepper. The prediction power of each SVM model was evaluated with a leave-10%-out cross-validation procedure. This multiclass dataset was modeled with an one-versus-all approach. 

Support Vector Machines for ffistogram-based Image Classification. 

Support Vector Machines Committee Classification Method for Computer-aided Polyp Detection in CT Colonography. 

Active Learning Support Vector Machines for Optimal Sample Selection in Classification. 

Xu, Y., Zomer, S., Brereton, R. G. Crit. Rev. Anal. Chem. 34, 2006, 177-188. Support vector machines A recent method for classification in chemometrics. 

Support vector machines In addition to more traditional classification methods like clustering or partitioning, other computational approaches have recently also become popular in chemoinformatics and support vector machines (SVMs) (Warmuth el al. 2003) are discussed here as an example. Typically, SVMs are applied as classifiers for binary property predictions, for example, to distinguish active from inactive compounds. Initially, a set of descriptors is selected and training set molecules are represented as vectors based on their calculated descriptor values. Then linear combinations of training set vectors are calculated to construct a hyperplane in descriptor space that best separates active and inactive compounds, as illustrated in Figure 1.9. 

Cai CZ, Han LY, Ji ZL, Chen X, Chen YZ. SVM-Prot Web-based support vector machine software for functional classification of a protein from its primary sequence. Nucleic Acids Res 2003 31 3692-7. 

Guyon I, Weston J, Barnhill S, Vapnik V. Gene selection for cancer classification using support vector machines. Machine Learning 2002 46 389-422. 

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