code: public double fBeta(double beta, int classLabel, double defaultValue) {
          double precision = precision(classLabel, -1);
          double recall = recall(classLabel, -1);
          if (precision == -1 || recall == -1) {
              return defaultValue;
          }
          return EvaluationUtils.fBeta(beta, precision, recall);
      }
docs: Calculate the f_beta for a given class, where f_beta is defined as:<br>
  (1+beta^2) * (precision * recall) / (beta^2 * precision + recall).<br>
  F1 is a special case of f_beta, with beta=1.0
  
  @param beta       Beta value to use
  @param classLabel Class label
  @param defaultValue Default value to use when precision or recall is undefined (0/0 for prec. or recall)
  @return F_beta