feat: Added capymoa wrapper for OUAE algorithm

src/capymoa/classifier/__init__.py

@@ -18,6 +18,7 @@
 from ._samknn import SAMkNN
 from ._dynamic_weighted_majority import DynamicWeightedMajority
 from ._csmote import CSMOTE
+from ._online_accuracy_updated_ensemble import OnlineAccuracyUpdatedEnsemble
 
 __all__ = [
     "AdaptiveRandomForestClassifier",
@@ -39,5 +40,6 @@
     "HoeffdingAdaptiveTree",
     "SAMkNN",
     "DynamicWeightedMajority",
-    "CSMOTE"
-]
+    "CSMOTE",
+    "OnlineAccuracyUpdatedEnsemble"
+]

src/capymoa/classifier/_online_accuracy_updated_ensemble.py

@@ -0,0 +1,81 @@
+from capymoa.base import MOAClassifier
+from moa.classifiers.meta import OnlineAccuracyUpdatedEnsemble as _MOA_OnlineAccuracyUpdatedEnsemble
+from capymoa.stream import Schema
+from capymoa._utils import build_cli_str_from_mapping_and_locals
+
+
+class OnlineAccuracyUpdatedEnsemble(MOAClassifier):
+    """OnlineAccuracyUpdatedEnsemble
+
+    The online version of the Accuracy Updated Ensemble as proposed by
+    Brzezinski and Stefanowski in "Combining block-based and online methods 
+    in learning ensembles from concept drifting data streams", Information Sciences, 2014.
+
+    Reference:
+
+    `Combining block-based and online methods in learning ensembles from concept drifting data streams.
+    Daruisz Brzezinski, Jerzy Stefanowski
+    IS, 2014.
+    <https://doi.org/10.1016/j.ins.2013.12.011>`_
+
+    Example usages:
+
+    >>> from capymoa.datasets import ElectricityTiny
+    >>> from capymoa.classifier import OnlineAccuracyUpdatedEnsemble
+    >>> from capymoa.evaluation import prequential_evaluation
+    >>> stream = ElectricityTiny()
+    >>> schema = stream.get_schema()
+    >>> learner = OnlineAccuracyUpdatedEnsemble(schema)
+    >>> results = prequential_evaluation(stream, learner, max_instances=1000)
+    >>> results["cumulative"].accuracy()
+    87.5
+    """
+
+
+    def __init__(
+        self,
+        schema: Schema,
+        random_seed: int = 1,
+        learner_option= 'trees.HoeffdingTree -e 2000000 -g 100 -c 0.01', 
+        member_count_option: int = 5,
+        window_size_option: float = 50.0,
+        max_byte_size_option: int = 33554432,
+        verbose_option: bool = False,
+        linear_option: bool = False,
+    ):
+
+
+        """ Online Accuracy Updated Ensemble Classifier
+
+        :param schema: The schema of the stream.
+        :param learner_option: Classifier to train.
+        :param member_count_option: The maximum number of classifiers in an ensemble.
+        :param window_size_option: The window size used for classifier creation and evaluation.
+        :param max_byte_size_option: Maximum memory consumed by ensemble.
+        :param verbose_option: When checked the algorithm outputs additional information about component classifier weights.
+        :param linear_option: When checked the algorithm uses a linear weighting function.
+        """
+
+
+        mapping = {
+            "learner_option": "-l",
+            "member_count_option": "-n",
+            "window_size_option": "-w",
+            "max_byte_size_option": "-m",
+            "verbose_option": "-v",
+            "linear_option": "-f",
+        }
+
+
+        assert (type(learner_option) == str
+            ), "Only MOA CLI strings are supported for SGBT base_learner, at the moment."
+
+
+        config_str = build_cli_str_from_mapping_and_locals(mapping, locals())
+        self.moa_learner = _MOA_OnlineAccuracyUpdatedEnsemble()
+        super(OnlineAccuracyUpdatedEnsemble, self).__init__(
+            schema=schema,
+            random_seed=random_seed,
+            CLI=config_str,
+            moa_learner=self.moa_learner,
+        )

tests/test_classifiers.py

@@ -18,7 +18,9 @@
     CSMOTE,
     LeveragingBagging,
     OnlineAdwinBagging,
+    OnlineAccuracyUpdatedEnsemble
 )
+
 from capymoa.base import Classifier
 from capymoa.base import MOAClassifier
 from capymoa.datasets import ElectricityTiny
@@ -62,6 +64,7 @@
         (partial(CSMOTE), 80.55, 79.0, None),
         (partial(LeveragingBagging), 86.7, 91.0, None),
         (partial(OnlineAdwinBagging), 85.25, 92.0, None),
+        (partial(OnlineAccuracyUpdatedEnsemble), 85.25, 92.0, None),
     ],
     ids=[
         "OnlineBagging",
@@ -77,6 +80,7 @@
         "OzaBoost",
         "MajorityClass",
         "NoChange",
+        "OnlineAccuracyUpdatedEnsemble",
         "OnlineSmoothBoost",
         "StreamingRandomPatches",
         "HoeffdingAdaptiveTree",