diff --git a/proglearn/base.py b/proglearn/base.py index 84a1a12629..d4221132b3 100644 --- a/proglearn/base.py +++ b/proglearn/base.py @@ -146,7 +146,7 @@ def is_fitted(self): pass -class ClassificationDecider(BaseDecider): +class BaseClassificationDecider(BaseDecider): """ A class for a decider which inherits from the base decider but adds the functionality of estimating posteriors. @@ -219,7 +219,7 @@ def predict(self, X, task_id): pass -class ClassificationProgressiveLearner(BaseProgressiveLearner): +class BaseClassificationProgressiveLearner(BaseProgressiveLearner): """ A class for a progressive learner which inherits from the base progressive learner but adds the functionality of estimating posteriors for a given task_id. diff --git a/proglearn/deciders.py b/proglearn/deciders.py index 2389c0a7c7..f466c9867c 100755 --- a/proglearn/deciders.py +++ b/proglearn/deciders.py @@ -4,7 +4,7 @@ ''' import numpy as np -from .base import ClassificationDecider +from .base import BaseClassificationDecider from sklearn.neighbors import KNeighborsRegressor from sklearn.linear_model import Ridge @@ -18,7 +18,7 @@ from sklearn.utils.multiclass import type_of_target -class SimpleArgmaxAverage(ClassificationDecider): +class SimpleArgmaxAverage(BaseClassificationDecider): """ Doc string here. """ diff --git a/proglearn/progressive_learner.py b/proglearn/progressive_learner.py index e0156ebc0c..8362d23829 100755 --- a/proglearn/progressive_learner.py +++ b/proglearn/progressive_learner.py @@ -3,9 +3,9 @@ Corresponding Email: levinewill@icloud.com ''' import numpy as np -from .base import ClassificationDecider, ClassificationProgressiveLearner +from .base import BaseClassificationDecider, BaseClassificationProgressiveLearner -class ProgressiveLearner(ClassificationProgressiveLearner): +class ProgressiveLearner(BaseClassificationProgressiveLearner): """ A class for progressive learning in the classification setting. @@ -667,7 +667,7 @@ def predict(self, X, task_id, transformer_ids=None): def predict_proba(self, X, task_id, transformer_ids=None): decider = self.task_id_to_decider[task_id] - if isinstance(decider, ClassificationDecider): + if isinstance(decider, BaseClassificationDecider): return self.task_id_to_decider[task_id].predict_proba( X, transformer_ids=transformer_ids )