def train(self, X, Y):
        try:

        if self.toolset == 'sklearn':
            return self._train_sklearn(X, Y)
        elif self.toolset == 'opencv':
            return self._train_opencv(X, Y)
        elif self.toolset == 'libsvm':
            return self._train_libscm(X, Y)
        elif self.toolset == 'spark':
            return self._train_spark(X, Y)
        else:
            raise Exception("Unknown toolset!")

    def predict(self, feat, model=None):

        if self.toolset == 'sklearn':
            return self._predict_sklearn(feat, model)
        elif self.toolset == 'opencv':
            return self._predict_opencv(feat, model)
        elif self.toolset == 'libsvm':
            return self._predict_libsvm(feat, model)
        elif self.toolset == 'libsvm':
            return self._predict_spark(feat, model)
        else:
            raise Exception("Unknown toolset!")


    def test(self, X, Y, model=None):

        if self.toolset == 'sklearn':
            return self._test_sklearn(X, Y, model)
        elif self.toolset == 'opencv':
            return self._test_opencv(X, Y, model)
        elif self.toolset == 'libsvm':
            return self._test_libsvm(X, Y, model)
        elif self.toolset == 'libsvm':
            return self._test_spark(X, Y, model)
        else:
            raise Exception("Unknown toolset!")


COMPRESSED=/home/hadoop/workspace/pycharm/tmp/ImageR/mdata.zip,/home/hadoop/workspace/pycharm/tmp/ImageR/mfeat.zip,/home/hadoop/workspace/pycharm/tmp/ImageR/mjpeg.zip,/home/hadoop/workspace/pycharm/tmp/ImageR/msteg.zip,/home/hadoop/workspace/pycharm/tmp/ImageR/mmodel.zip,/home/hadoop/workspace/pycharm/tmp/ImageR/mspark.zip