def prob_classify_many(self, featuresets):
        return [self.prob_classify(fs) for fs in featuresets]


# # [XX] IN PROGRESS:
# class SequenceClassifierI(object):
#     """
#     A processing interface for labeling sequences of tokens with a
#     single category label (or "class").  Labels are typically
#     strs or ints, but can be any immutable type.  The set
#     of labels that the classifier chooses from must be fixed and
#     finite.
#     """
#     def labels(self):
#         """
#         :return: the list of category labels used by this classifier.
#         :rtype: list of (immutable)
#         """
#         raise NotImplementedError()

#     def prob_classify(self, featureset):
#         """
#         Return a probability distribution over labels for the given
#         featureset.

#         If ``featureset`` is a list of featuresets, then return a
#         corresponding list containing the probability distribution
#         over labels for each of the given featuresets, where the
#         *i*\ th element of this list is the most appropriate label for
#         the *i*\ th element of ``featuresets``.
#         """
#         raise NotImplementedError()

#     def classify(self, featureset):
#         """
#         Return the most appropriate label for the given featureset.

#         If ``featureset`` is a list of featuresets, then return a
#         corresponding list containing the most appropriate label for
#         each of the given featuresets, where the *i*\ th element of
#         this list is the most appropriate label for the *i*\ th element
#         of ``featuresets``.
#         """
#         raise NotImplementedError()
Get metrics for a specific instance of a worker pool of a
dataset/ETHPy150Open nltk/nltk/nltk/classify/api.py/MultiClassifierI.prob_classify_many--crossover with--dataset/ETHPy150Open Azure/azure-sdk-for-python/azure-mgmt-web/azure/mgmt/web/operations/hosting_environments_operations.py/HostingEnvironmentsOperations.get_worker_pool_instance_metrics