docs: public Vote getVotes(Instance instance) {
  		ErrorWeightedVote errorWeightedVote=newErrorWeightedVote();
  		//DoubleVector combinedVote = new DoubleVector();
  		debug("Test",3);    
  		int numberOfRulesCovering = 0;
  
  		VerboseToConsole(instance); // Verbose to console Dataset name.
  		for (Rule rule : ruleSet) {
  			if (rule.isCovering(instance) == true){
  				numberOfRulesCovering++;
  				//DoubleVector vote = new DoubleVector(rule.getPrediction(instance));
  				double [] vote=rule.getPrediction(instance);
  				double error= rule.getCurrentError();
  				debug("Rule No"+ rule.getRuleNumberID() + " Vote: " + Arrays.toString(vote) + " Error: " + error + " Y: " + instance.classValue(),3); //predictionValueForThisRule);
  				errorWeightedVote.addVote(vote,error);
  				//combinedVote.addValues(vote);
  				if (!this.unorderedRulesOption.isSet()) { // Ordered Rules Option.
  					break; // Only one rule cover the instance.
  				}
  			}
  		}
  
  		if (numberOfRulesCovering == 0) {
  			//combinedVote = new DoubleVector(defaultRule.getPrediction(instance));
  			double [] vote=defaultRule.getPrediction(instance);
  			double error= defaultRule.getCurrentError();
  			errorWeightedVote.addVote(vote,error);
  			
  			debug("Default Rule Vote " + Arrays.toString(vote) + " Error " + error + "  Y: " + instance.classValue(),3);
  		} 	
  		double[] weightedVote=errorWeightedVote.computeWeightedVote();
  		double weightedError=errorWeightedVote.getWeightedError();
  		
  		debug("Weighted Rule - Vote: " + Arrays.toString(weightedVote) + " Weighted Error: " + weightedError + " Y:" + instance.classValue(),3);
  		return new Vote(weightedVote, weightedError);
  	}