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diff --git a/resources/libraries/python/jumpavg/classify.py b/resources/libraries/python/jumpavg/classify.py
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+# Copyright (c) 2019 Cisco and/or its affiliates.
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at:
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Module holding the classify function
+
+Classification os one of primary purposes of this package.
+
+Minimal message length principle is used
+for grouping results into the list of groups,
+assuming each group is a population of different Gaussian distribution.
+"""
+
+from .AvgStdevStats import AvgStdevStats
+from .BitCountingGroupList import BitCountingGroupList
+
+
+def classify(values):
+    """Return the values in groups of optimal bit count.
+
+    Here, a value is either a float, or an iterable of floats.
+    Such iterables represent an undivisible sequence of floats.
+
+    Internally, such sequence is replaced by AvgStdevStats
+    after maximal value is found.
+
+    :param values: Sequence of runs to classify.
+    :type values: Iterable[Union[float, Iterable[float]]]
+    :returns: Classified group list.
+    :rtype: BitCountingGroupList
+    """
+    processed_values = list()
+    max_value = 0.0
+    for value in values:
+        if isinstance(value, (float, int)):
+            if value > max_value:
+                max_value = value
+            processed_values.append(value)
+        else:
+            for subvalue in value:
+                if subvalue > max_value:
+                    max_value = subvalue
+            processed_values.append(AvgStdevStats.for_runs(value))
+    open_at = list()
+    closed_before = [BitCountingGroupList(max_value=max_value)]
+    for index, value in enumerate(processed_values):
+        newly_open = closed_before[index].copy()
+        newly_open.append_group_of_runs([value])
+        open_at.append(newly_open)
+        record_group_list = newly_open
+        for previous_index, old_open in enumerate(open_at[:index]):
+            new_open = old_open.copy().append_run_to_to_last_group(value)
+            open_at[previous_index] = new_open
+            if new_open.bits < record_group_list.bits:
+                record_group_list = new_open
+        closed_before.append(record_group_list)
+    partition = closed_before[-1]
+    previous_average = partition[0].stats.avg
+    for group in partition:
+        if group.stats.avg == previous_average:
+            group.comment = u"normal"
+        elif group.stats.avg < previous_average:
+            group.comment = u"regression"
+        elif group.stats.avg > previous_average:
+            group.comment = u"progression"
+        previous_average = group.stats.avg
+    return partition