question: public EvoSVMModel ( ExampleSet exampleSet , List < SupportVector > supportVectors , Kernel kernel , double bias ) { super ( exampleSet , ExampleSetUtilities . SetsCompareOption . ALLOW_SUPERSET , ExampleSetUtilities . TypesCompareOption . ALLOW_SAME_PARENTS ) ; this . supportVectors = supportVectors ; if ( supportVectors == null || supportVectors . size ( ) == 0 ) { throw new IllegalArgumentException ( "Null or empty support vector collection: not possible to predict values!" ) ; } this . kernel = kernel ; this . bias = bias ; if ( this . kernel instanceof DotKernel ) { this . weights = new double [ getNumberOfAttributes ( ) ] ; for ( int i = 0 ; i < getNumberOfSupportVectors ( ) ; i ++ ) { SupportVector sv = getSupportVector ( i ) ; if ( sv != null ) { double [ ] x = sv . getX ( ) ; double alpha = sv . getAlpha ( ) ; double y = sv . getY ( ) ; for ( int j = 0 ; j < weights . length ; j ++ ) { weights [ j ] += y * alpha * x [ j ] ; } } else { this . weights = null ; break ; } } } }
target:  Creates a classification model. 