شماره ركورد كنفرانس :
453
عنوان مقاله :
Interval Support Vector Machine in Regression Analysis
پديدآورندگان :
Arjmandzadeh A نويسنده , Zamirian M نويسنده
كليدواژه :
Support Vector Machine , Regression analysis , Interval quadratic optimization problem
عنوان كنفرانس :
چهارمين كنفرانس بين المللي انجمن ايران تحقيق در عمليات
چكيده فارسي :
Support vector machines (SVMs) have been widely applied in regression analysis. The
standard support vector regression (SVR), is a quadratic optimization problem that is formulated
according to the form of training samples. In real world, the parameters are seldom known and usually
are estimated. In this paper we propose an interval support vector regression (ISVR) problem which the
training samples are interval values. Using duality theorem and applying variable transformation
theorem the problem is solved
شماره مدرك كنفرانس :
1891451