An Interior Point Method for <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-4.67648pt;width:35.075001px;" id="M1" height="22.637501" version="1.1" viewBox="0 0 35.075001 22.637501" width="35.075001">
	
		
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			<g transform="matrix(.016,-0,0,-.016,12.862,20.012)"><path id="x31" d="M384 0h-275v27q67 5 81.5 18.5t14.5 68.5v385q0 38 -7.5 47.5t-40.5 10.5l-48 2v24q85 15 178 52v-521q0 -55 14.5 -68.5t82.5 -18.5v-27z"></path></g><g transform="matrix(.016,-0,0,-.016,20.394,20.012)"><path id="x2F" d="M368 703l-264 -866h-60l265 866h59z"></path></g><g transform="matrix(.016,-0,0,-.016,26.859,20.012)"><path id="x32" d="M412 140l28 -9q0 -2 -35 -131h-373v23q112 112 161 170q59 70 92 127t33 115q0 63 -31 98t-86 35q-75 0 -137 -93l-22 20l57 81q55 59 135 59q69 0 118.5 -46.5t49.5 -122.5q0 -62 -29.5 -114t-102.5 -130l-141 -149h186q42 0 58.5 10.5t38.5 56.5z"></path></g>

		
	
</svg>-SVM and Application to Feature Selection in Classification

<table>Results comparison on artificial data set with various dimensions.</table>

Journal of Applied Mathematics

fig3

Figure 3

Figure 3: An Interior Point Method for <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-4.67648pt;width:35.075001px;" id="M1" height="22.637501" version="1.1" viewBox="0 0 35.075001 22.637501" width="35.075001">
	
		
			<g transform="matrix(.022,-0,0,-.022,.062,14.638)"><path id="x1D43F" d="M559 163q-23 -66 -68 -163h-474l6 26q62 4 79.5 19.5t28.5 75.5l78 409q7 35 8.5 49t-8 25t-24 13t-51.5 5l5 28h266l-6 -28q-65 -5 -79.5 -18t-25.5 -74l-76 -406q-10 -57 14 -75q12 -13 96 -13q93 0 126 29q41 40 76 109z"></path></g>

			<g transform="matrix(.016,-0,0,-.016,12.862,20.012)"><path id="x31" d="M384 0h-275v27q67 5 81.5 18.5t14.5 68.5v385q0 38 -7.5 47.5t-40.5 10.5l-48 2v24q85 15 178 52v-521q0 -55 14.5 -68.5t82.5 -18.5v-27z"></path></g><g transform="matrix(.016,-0,0,-.016,20.394,20.012)"><path id="x2F" d="M368 703l-264 -866h-60l265 866h59z"></path></g><g transform="matrix(.016,-0,0,-.016,26.859,20.012)"><path id="x32" d="M412 140l28 -9q0 -2 -35 -131h-373v23q112 112 161 170q59 70 92 127t33 115q0 63 -31 98t-86 35q-75 0 -137 -93l-22 20l57 81q55 59 135 59q69 0 118.5 -46.5t49.5 -122.5q0 -62 -29.5 -114t-102.5 -130l-141 -149h186q42 0 58.5 10.5t38.5 56.5z"></path></g>

		
	
</svg>-SVM and Application to Feature Selection in Classification 

Journal of Applied Mathematics

An Interior Point Method for -SVM and Application to Feature Selection in Classification

Figure 3