public KernelLogisticRegressionModel(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;
}

public KernelLogisticRegressionModel ( 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 ; }
creates a classification model .
