New imbalance_bagging.py

summit/multiview_platform/monoview_classifiers/imbalance_bagging.py

+from imblearn.ensemble import BalancedBaggingClassifier
+from sklearn.tree import DecisionTreeClassifier
+
+from ..monoview.monoview_utils import BaseMonoviewClassifier
+from ..utils.base import base_boosting_estimators
+from ..utils.hyper_parameter_search import CustomRandint, CustomUniform
+
+classifier_class_name = "ImbalanceBagging"
+
+class ImbalanceBagging(BaseMonoviewClassifier, BalancedBaggingClassifier):
+
+    def __init__(self, random_state=None, base_estimator="DecisionTreeClassifier",
+                 n_estimators=10, sampling_strategy="auto",
+                 replacement=False, base_estimator_config=None):
+        base_estimator = self.get_base_estimator(base_estimator,
+                                                 base_estimator_config)
+        super(ImbalanceBagging, self).__init__(random_state=random_state, base_estimator=base_estimator,
+                                         n_estimators=n_estimators,
+                                         sampling_strategy=sampling_strategy,
+                                         replacement=replacement)
+
+        self.param_names = ["n_estimators", "base_estimator", "sampling_strategy",]
+        self.classed_params = ["base_estimator"]
+        self.distribs = [CustomRandint(low=1, high=50),
+                         base_boosting_estimators,
+                         ["auto"]]
+        self.weird_strings = {"base_estimator": "class_name"}
+        self.base_estimator_config = base_estimator_config
+
+
+