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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _vote_disagreement(self, votes):
 """ Return the disagreement measurement of the given number of votes. It uses the vote vote to measure the disagreement. Parameters votes : list of int, shape==(n_samples, n_students) The predictions that each student gives to each sample. Returns ------- disagreement : list of float, shape=(n_samples) The vote entropy of the given votes. """

        ret = []
        for candidate in votes:
            ret.append(0.0)
            lab_count = {}
            for lab in candidate:
                lab_count[lab] = lab_count.setdefault(lab, 0) + 1

            # Using vote entropy to measure disagreement
            for lab in lab_count.keys():
                ret[-1] -= lab_count[lab] / self.n_students * \
                    math.log(float(lab_count[lab]) / self.n_students)

        return ret