code: private double[] getVotesForInstance(Instance instance) {
  		ErrorWeightedVote errorWeightedVote=newErrorWeightedVote(); 
  		int numberOfRulesCovering = 0;
  		
  		for (ActiveRule rule: ruleSet) {
  			if (rule.isCovering(instance) == true){
  				numberOfRulesCovering++;
  				double [] vote=rule.getPrediction(instance);
  				double error= rule.getCurrentError();
  				errorWeightedVote.addVote(vote,error);
  				if (!this.unorderedRules) { // Ordered Rules Option.
  					break; // Only one rule cover the instance.
  				}
  			}
  		}
  
  		if (numberOfRulesCovering == 0) {
  			double [] vote=defaultRule.getPrediction(instance);
  			double error= defaultRule.getCurrentError();
  			errorWeightedVote.addVote(vote,error);	
  		} 	
  		double[] weightedVote=errorWeightedVote.computeWeightedVote();
  		
  		return weightedVote;
  	}
docs: getVotesForInstance extension of the instance method getVotesForInstance
  in moa.classifier.java
  returns the prediction of the instance.
  Called in EvaluateModelRegression