refactor code name for clarification

yzhao062 · Jul 29, 2019 · f0c447a · f0c447a
1 parent 74989f9
commit f0c447a
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Showing 8 changed files with 10 additions and 10 deletions.
diff --git a/combo/models/stacking.py → combo/models/classifier_stacking.py b/combo/models/stacking.py → combo/models/classifier_stacking.py
diff --git a/combo/test/test_stacking.py b/combo/test/test_stacking.py
@@ -32,7 +32,7 @@
 # if  combo is installed, no need to use the following line
 sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
 
-from combo.models.stacking import Stacking
+from combo.models.classifier_stacking import Stacking
 from combo.utils.data import evaluate_print
 
 

diff --git a/docs/api.rst b/docs/api.rst
@@ -11,7 +11,7 @@ Classifier Combination
 
 * :class:`combo.models.classifier_comb.SimpleClassifierAggregator`: a collection of classifier
   combination methods, e.g., average, median, and majority vote.
-* :class:`combo.models.stacking.Stacking`: Stacking (meta ensembling). Check this `introductory
+* :class:`combo.models.classifier_stacking.Stacking`: Stacking (meta ensembling). Check this `introductory
   article by Kaggle <http://blog.kaggle.com/2016/12/27/a-kagglers-guide-to-model-stacking-in-practice/>`_.
 
 

diff --git a/docs/combo.models.rst b/docs/combo.models.rst
@@ -20,10 +20,10 @@ combo.models.detector\_comb module
    :show-inheritance:
    :inherited-members:
 
-combo.models.stacking module
-----------------------------
+combo.models.classifier\_stacking module
+----------------------------------------
 
-.. automodule:: combo.models.stacking
+.. automodule:: combo.models.classifier_stacking
    :members:
    :undoc-members:
    :show-inheritance:

diff --git a/docs/example.rst b/docs/example.rst
@@ -36,7 +36,7 @@ demonstrates the basic API of stacking (meta ensembling).
    .. code-block:: python
 
 
-       from combo.models.stacking import Stacking
+       from combo.models.classifier_stacking import Stacking
 
        clf = Stacking(base_estimators=classifiers, n_folds=4, shuffle_data=False,
                    keep_original=True, use_proba=False, random_state=random_state)

diff --git a/docs/index.rst b/docs/index.rst
@@ -105,7 +105,7 @@ combo is featured for:
    .. code-block:: python
 
 
-       from combo.models.stacking import Stacking
+       from combo.models.classifier_stacking import Stacking
        # base classifiers
        classifiers = [DecisionTreeClassifier(), LogisticRegression(),
                       KNeighborsClassifier(), RandomForestClassifier(),
@@ -161,7 +161,7 @@ General Purpose      Majority Vote & Weighted Majority Vote
 Classification       SimpleClassifierAggregator: combining classifiers by general purpose methods above                      N/A    N/A                                          :class:`combo.models.classifier_comb.SimpleClassifierAggregator`
 Classification       DCS: Dynamic Classifier Selection (Combination of multiple classifiers using local accuracy estimates)  1997   :cite:`a-woods1997combination` (WIP)
 Classification       DES: Dynamic Ensemble Selection (From dynamic classifier selection to dynamic ensemble selection)       2008   :cite:`a-ko2008dynamic` (WIP)
-Classification       Stacking (meta ensembling): use a meta learner to learn the base classifier results                     N/A    :cite:`a-gorman2016kaggle`                   :class:`combo.models.stacking.Stacking`
+Classification       Stacking (meta ensembling): use a meta learner to learn the base classifier results                     N/A    :cite:`a-gorman2016kaggle`                   :class:`combo.models.classifier_stacking.Stacking`
 Clustering           Clusterer Ensemble: combine the results of multiple clustering results by relabeling                    2006   :cite:`a-zhou2006clusterer`                  :class:`combo.models.cluster_comb.ClustererEnsemble`
 Anomaly Detection    SimpleDetectorCombination: combining outlier detectors by general purpose methods above                 N/A    :cite:`a-aggarwal2017outlier`                :class:`combo.models.detector_comb.SimpleDetectorAggregator`
 Anomaly Detection    Average of Maximum (AOM): divide base detectors into subgroups to take the maximum, and then average    2015   :cite:`a-aggarwal2015theoretical`            :mod:`combo.models.score_comb.aom`

diff --git a/examples/compare_selected_classifiers.py b/examples/compare_selected_classifiers.py
@@ -35,7 +35,7 @@
 from sklearn.neighbors import KNeighborsClassifier
 
 from combo.models.classifier_comb import SimpleClassifierAggregator
-from combo.models.stacking import Stacking
+from combo.models.classifier_stacking import Stacking
 
 # Define the number of class 0 and class 1
 n_samples = 300

diff --git a/examples/stacking_example.py b/examples/stacking_example.py
@@ -22,7 +22,7 @@
 from sklearn.model_selection import train_test_split
 from sklearn.datasets import load_breast_cancer
 
-from combo.models.stacking import Stacking
+from combo.models.classifier_stacking import Stacking
 from combo.utils.data import evaluate_print
 
 import warnings