def calculateJointProbabilities(self, instance):
        """
        Returns the joint distribution over legal labels and the instance.
        Each probability should be stored in the joint counter, e.g.
        Joint[3] = <Estimate of ( P(Label = 3, instance) )>

        To get the list of all possible features or labels, use self.features and
        self.legalLabels.
        """
        joint = util.Counter()

        for label in self.legalLabels:
            # calculate the joint probabilities for each class
            prob = self.prior[label]
            for feat in self.features:
                prob *= self.conditionalProb[(feat, label, instance[feat])]
            joint[label] = prob

        return joint


    def calculateLogJointProbabilities(self, instance):
        """
        Returns the log-joint distribution over legal labels and the instance.
        Each log-probability should be stored in the log-joint counter, e.g.
        logJoint[3] = <Estimate of log( P(Label = 3, instance) )>

        To get the list of all possible features or labels, use self.features and
        self.legalLabels.
        """
        logJoint = util.Counter()

        for label in self.legalLabels:
            #calculate the log joint probabilities for each class
            prob = math.log(self.prior[label])
            for feat in self.features:
                prob += math.log(self.conditionalProb[(feat, label, instance[feat])])

            logJoint[label] = prob

        return logJoint