code: @Override
      public double[] getVotesForInstance(Instance inst) {
  
          if (m_weights == null) {
              return new double[inst.numClasses()];
          }
          double[] result = (inst.classAttribute().isNominal())
                  ? new double[2]
                  : new double[1];
  
  
          double wx = dotProd(inst, m_weights, inst.classIndex());// * m_wScale;
          double z = (wx + m_bias);
  
          if (inst.classAttribute().isNumeric()) {
              result[0] = z;
              return result;
          }
  
          if (z <= 0) {
              //  z = 0;
              if (m_loss == LOGLOSS) {
                  result[0] = 1.0 / (1.0 + Math.exp(z));
                  result[1] = 1.0 - result[0];
              } else {
                  result[0] = 1;
              }
          } else {
              if (m_loss == LOGLOSS) {
                  result[1] = 1.0 / (1.0 + Math.exp(-z));
                  result[0] = 1.0 - result[1];
              } else {
                  result[1] = 1;
              }
          }
          return result;
      }
docs: Calculates the class membership probabilities for the given test
  instance.
  
  @param instance 	the instance to be classified
  @return 		predicted class probability distribution