def predictScore(self, message):
        if (self._localClassifier is None):
            return self._globalClassifier.predictScore(message)
        else:
            #--- compute interpolated decision value
            globalDecisionFunction = self._globalClassifier.predictScore(
                message)['pos']
            localDecisionFunction = self._localClassifier.predictScore(
                message)['pos']
            df = (1 - self._alpha) * globalDecisionFunction + \
                self._alpha * localDecisionFunction

            #--- return dictionary of score
            scoreDic = {}
            scoreDic['pos'] = df
            scoreDic['neg'] = -df
            return scoreDic
dataset/ETHPy150Open dssg/ushine-learning/dssg/classifier.py/DssgBinaryClassifierAdaptiveInterpolation.predictScore/original