public double[] getVotesForInstance_ori(Instance inst) {
        DoubleVector combinedVote = new DoubleVector();
        DoubleVector confidenceVec = new DoubleVector();
        double[] ensembleVotes = new double[inst.numClasses()];
        double qbcEntropy = 0.0;
        int success = 0;
        double confidence = 0.0;

        for (int i = 0; i < this.ensemble.length; i++) {
            DoubleVector vote = new DoubleVector(this.ensemble[i]
                    .getVotesForInstance(inst));
            if (vote.sumOfValues() > 0.0) {
                vote.normalize();
                combinedVote.addValues(vote);
                if ((this.useWeightOption != null)
                        && this.useWeightOption.isSet()) {
                    vote.scaleValues(1.0 / (this.error[i] * this.error[i]));
                }
                if (this.error[i] < errorRatio && ((ASHoeffdingOptionTree) this.ensemble[i]).measureTreeDepth() > 2) {
                    //
                    // these are the votes of the ensembles for the classes
                    //
                    success++;
                    confidenceVec.addValues(vote);
                    ensembleVotes[confidenceVec.maxIndex()] += confidenceVec.getValue(confidenceVec.maxIndex());
                }
            }
        }
        if (confidenceVec.numValues() > 0) {
            confidenceVec = (DoubleVector) combinedVote.copy();
            confidenceVec.normalize();
            confidence = (confidenceVec.maxValue());
        }

        //Reconfigure the activeLearningRatio
        //For confidence measure add to the pool  and in order to fit the confidence value between 0 and 1 divide by success val
        if (confidence >= confidenceThreshold) {
            qbcEntropy = QBC.queryByCommitee(ensembleVotes, inst.numClasses(), success, ensemble.length);
            double activeLearningRatio = getActiveLearningRatio(qbcEntropy, combinedVote);
            inst.setClassValue(combinedVote.maxIndex()); //Set the class value of the instance
            instConfPool.addVotedInstance(inst, combinedVote
                    .getValue(combinedVote.maxIndex()), activeLearningRatio);
            instConfCount++;
        }
        return confidenceVec.getArrayRef();//combinedVote.getArrayRef();
    }