<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kumar, Pankaj</style></author><author><style face="normal" font="default" size="100%">Jayaraman, Valadi K.</style></author><author><style face="normal" font="default" size="100%">Kulkarni, B. D.</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Ghosh, A.</style></author><author><style face="normal" font="default" size="100%">De, R. K.</style></author><author><style face="normal" font="default" size="100%">Pal, S. K.</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Granular support vector machine based method for prediction of solubility of proteins on overexpression in Escherichia coli</style></title><secondary-title><style face="normal" font="default" size="100%">Pattern Recognition and Machine Intelligence, Proceedings</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">LECTURE NOTES IN COMPUTER SCIENCE</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">DEC</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Indian Stat Inst, Machine Intelligence Univ; ISI Ctr Soft Comp Res; Int Assoc Pattern Recognit; Int Ctr Pure &amp; Appl Math; Web Intelligence Consortium; Yahoo India Res &amp; Dev; Philips Res Asia</style></publisher><pub-location><style face="normal" font="default" size="100%">Heidelberger Platz 3, D-14197 Berlin, Germany</style></pub-location><volume><style face="normal" font="default" size="100%">4815</style></volume><pages><style face="normal" font="default" size="100%">406-415</style></pages><isbn><style face="normal" font="default" size="100%">978-3-540-77045-9</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We employed a granular support vector Machines(GSVM) for prediction of soluble proteins on over expression in Escherichia coli. Granular computing splits the feature space into a set of subspaces (or information granules) such as classes, subsets, clusters and intervals [14]. By the principle of divide and conquer it decomposes a. bigger complex problem into smaller and computationally simpler problems. Each of the granules is then solved independently and all the results are aggregated to form the final solution. For the purpose of granulation association rules was employed. The results indicate that a difficult imbalanced classification problem can be successfully solved by employing GSVM.&lt;/p&gt;</style></abstract><notes><style face="normal" font="default" size="100%">2nd International Conference on Pattern Recognition and Machine Intelligence, Calcutta, INDIA, DEC 18-22, 2007</style></notes></record></records></xml>