Merge pull request #72 from zStupan/master

Removed deprecated sklearn warnings

Author: firefly-cpp

niaaml/classifiers/ada_boost.py

@@ -6,13 +6,11 @@
 
 import warnings
 from sklearn.exceptions import (
-    ChangedBehaviorWarning,
     ConvergenceWarning,
     DataConversionWarning,
     DataDimensionalityWarning,
     EfficiencyWarning,
     FitFailedWarning,
-    NonBLASDotWarning,
     UndefinedMetricWarning,
 )
 
@@ -44,13 +42,11 @@ class AdaBoost(Classifier):
 
     def __init__(self, **kwargs):
         r"""Initialize AdaBoost instance."""
-        warnings.filterwarnings(action="ignore", category=ChangedBehaviorWarning)
         warnings.filterwarnings(action="ignore", category=ConvergenceWarning)
         warnings.filterwarnings(action="ignore", category=DataConversionWarning)
         warnings.filterwarnings(action="ignore", category=DataDimensionalityWarning)
         warnings.filterwarnings(action="ignore", category=EfficiencyWarning)
         warnings.filterwarnings(action="ignore", category=FitFailedWarning)
-        warnings.filterwarnings(action="ignore", category=NonBLASDotWarning)
         warnings.filterwarnings(action="ignore", category=UndefinedMetricWarning)
 
         self._params = dict(

niaaml/classifiers/bagging.py

@@ -6,13 +6,11 @@
 
 import warnings
 from sklearn.exceptions import (
-    ChangedBehaviorWarning,
     ConvergenceWarning,
     DataConversionWarning,
     DataDimensionalityWarning,
     EfficiencyWarning,
     FitFailedWarning,
-    NonBLASDotWarning,
     UndefinedMetricWarning,
 )
 
@@ -44,13 +42,11 @@ class Bagging(Classifier):
 
     def __init__(self, **kwargs):
         r"""Initialize Bagging instance."""
-        warnings.filterwarnings(action="ignore", category=ChangedBehaviorWarning)
         warnings.filterwarnings(action="ignore", category=ConvergenceWarning)
         warnings.filterwarnings(action="ignore", category=DataConversionWarning)
         warnings.filterwarnings(action="ignore", category=DataDimensionalityWarning)
         warnings.filterwarnings(action="ignore", category=EfficiencyWarning)
         warnings.filterwarnings(action="ignore", category=FitFailedWarning)
-        warnings.filterwarnings(action="ignore", category=NonBLASDotWarning)
         warnings.filterwarnings(action="ignore", category=UndefinedMetricWarning)
 
         self._params = dict(

niaaml/classifiers/decision_tree.py

@@ -4,13 +4,11 @@
 
 import warnings
 from sklearn.exceptions import (
-    ChangedBehaviorWarning,
     ConvergenceWarning,
     DataConversionWarning,
     DataDimensionalityWarning,
     EfficiencyWarning,
     FitFailedWarning,
-    NonBLASDotWarning,
     UndefinedMetricWarning,
 )
 
@@ -42,13 +40,11 @@ class DecisionTree(Classifier):
 
     def __init__(self, **kwargs):
         r"""Initialize DecisionTree instance."""
-        warnings.filterwarnings(action="ignore", category=ChangedBehaviorWarning)
         warnings.filterwarnings(action="ignore", category=ConvergenceWarning)
         warnings.filterwarnings(action="ignore", category=DataConversionWarning)
         warnings.filterwarnings(action="ignore", category=DataDimensionalityWarning)
         warnings.filterwarnings(action="ignore", category=EfficiencyWarning)
         warnings.filterwarnings(action="ignore", category=FitFailedWarning)
-        warnings.filterwarnings(action="ignore", category=NonBLASDotWarning)
         warnings.filterwarnings(action="ignore", category=UndefinedMetricWarning)
 
         self._params = dict(

niaaml/classifiers/extremely_randomized_trees.py

@@ -6,13 +6,11 @@
 
 import warnings
 from sklearn.exceptions import (
-    ChangedBehaviorWarning,
     ConvergenceWarning,
     DataConversionWarning,
     DataDimensionalityWarning,
     EfficiencyWarning,
     FitFailedWarning,
-    NonBLASDotWarning,
     UndefinedMetricWarning,
 )
 
@@ -44,13 +42,11 @@ class ExtremelyRandomizedTrees(Classifier):
 
     def __init__(self, **kwargs):
         r"""Initialize ExtremelyRandomizedTrees instance."""
-        warnings.filterwarnings(action="ignore", category=ChangedBehaviorWarning)
         warnings.filterwarnings(action="ignore", category=ConvergenceWarning)
         warnings.filterwarnings(action="ignore", category=DataConversionWarning)
         warnings.filterwarnings(action="ignore", category=DataDimensionalityWarning)
         warnings.filterwarnings(action="ignore", category=EfficiencyWarning)
         warnings.filterwarnings(action="ignore", category=FitFailedWarning)
-        warnings.filterwarnings(action="ignore", category=NonBLASDotWarning)
         warnings.filterwarnings(action="ignore", category=UndefinedMetricWarning)
 
         self._params = dict(

niaaml/classifiers/gaussian_naive_bayes.py

@@ -3,13 +3,11 @@
 
 import warnings
 from sklearn.exceptions import (
-    ChangedBehaviorWarning,
     ConvergenceWarning,
     DataConversionWarning,
     DataDimensionalityWarning,
     EfficiencyWarning,
     FitFailedWarning,
-    NonBLASDotWarning,
     UndefinedMetricWarning,
 )
 
@@ -41,13 +39,11 @@ class GaussianNB(Classifier):
 
     def __init__(self, **kwargs):
         r"""Initialize GaussianNB instance."""
-        warnings.filterwarnings(action="ignore", category=ChangedBehaviorWarning)
         warnings.filterwarnings(action="ignore", category=ConvergenceWarning)
         warnings.filterwarnings(action="ignore", category=DataConversionWarning)
         warnings.filterwarnings(action="ignore", category=DataDimensionalityWarning)
         warnings.filterwarnings(action="ignore", category=EfficiencyWarning)
         warnings.filterwarnings(action="ignore", category=FitFailedWarning)
-        warnings.filterwarnings(action="ignore", category=NonBLASDotWarning)
         warnings.filterwarnings(action="ignore", category=UndefinedMetricWarning)
 
         self.__gaussian_nb = GNB()

niaaml/classifiers/gaussian_process.py

@@ -6,13 +6,11 @@
 
 import warnings
 from sklearn.exceptions import (
-    ChangedBehaviorWarning,
     ConvergenceWarning,
     DataConversionWarning,
     DataDimensionalityWarning,
     EfficiencyWarning,
     FitFailedWarning,
-    NonBLASDotWarning,
     UndefinedMetricWarning,
 )
 
@@ -44,13 +42,11 @@ class GaussianProcess(Classifier):
 
     def __init__(self, **kwargs):
         r"""Initialize GaussianProcess instance."""
-        warnings.filterwarnings(action="ignore", category=ChangedBehaviorWarning)
         warnings.filterwarnings(action="ignore", category=ConvergenceWarning)
         warnings.filterwarnings(action="ignore", category=DataConversionWarning)
         warnings.filterwarnings(action="ignore", category=DataDimensionalityWarning)
         warnings.filterwarnings(action="ignore", category=EfficiencyWarning)
         warnings.filterwarnings(action="ignore", category=FitFailedWarning)
-        warnings.filterwarnings(action="ignore", category=NonBLASDotWarning)
         warnings.filterwarnings(action="ignore", category=UndefinedMetricWarning)
 
         self._params = dict(

niaaml/classifiers/k_neighbors.py

@@ -4,13 +4,11 @@
 
 import warnings
 from sklearn.exceptions import (
-    ChangedBehaviorWarning,
     ConvergenceWarning,
     DataConversionWarning,
     DataDimensionalityWarning,
     EfficiencyWarning,
     FitFailedWarning,
-    NonBLASDotWarning,
     UndefinedMetricWarning,
 )
 
@@ -42,13 +40,11 @@ class KNeighbors(Classifier):
 
     def __init__(self, **kwargs):
         r"""Initialize KNeighbors instance."""
-        warnings.filterwarnings(action="ignore", category=ChangedBehaviorWarning)
         warnings.filterwarnings(action="ignore", category=ConvergenceWarning)
         warnings.filterwarnings(action="ignore", category=DataConversionWarning)
         warnings.filterwarnings(action="ignore", category=DataDimensionalityWarning)
         warnings.filterwarnings(action="ignore", category=EfficiencyWarning)
         warnings.filterwarnings(action="ignore", category=FitFailedWarning)
-        warnings.filterwarnings(action="ignore", category=NonBLASDotWarning)
         warnings.filterwarnings(action="ignore", category=UndefinedMetricWarning)
 
         self._params = dict(

niaaml/classifiers/linear_svc.py

@@ -6,13 +6,11 @@
 
 import warnings
 from sklearn.exceptions import (
-    ChangedBehaviorWarning,
     ConvergenceWarning,
     DataConversionWarning,
     DataDimensionalityWarning,
     EfficiencyWarning,
     FitFailedWarning,
-    NonBLASDotWarning,
     UndefinedMetricWarning,
 )
 
@@ -44,13 +42,11 @@ class LinearSVC(Classifier):
 
     def __init__(self, **kwargs):
         r"""Initialize LinearSVCClassifier instance."""
-        warnings.filterwarnings(action="ignore", category=ChangedBehaviorWarning)
         warnings.filterwarnings(action="ignore", category=ConvergenceWarning)
         warnings.filterwarnings(action="ignore", category=DataConversionWarning)
         warnings.filterwarnings(action="ignore", category=DataDimensionalityWarning)
         warnings.filterwarnings(action="ignore", category=EfficiencyWarning)
         warnings.filterwarnings(action="ignore", category=FitFailedWarning)
-        warnings.filterwarnings(action="ignore", category=NonBLASDotWarning)
         warnings.filterwarnings(action="ignore", category=UndefinedMetricWarning)
 
         self._params = dict(

niaaml/classifiers/multi_layer_perceptron.py

@@ -4,13 +4,11 @@
 
 import warnings
 from sklearn.exceptions import (
-    ChangedBehaviorWarning,
     ConvergenceWarning,
     DataConversionWarning,
     DataDimensionalityWarning,
     EfficiencyWarning,
     FitFailedWarning,
-    NonBLASDotWarning,
     UndefinedMetricWarning,
 )
 
@@ -42,13 +40,11 @@ class MultiLayerPerceptron(Classifier):
 
     def __init__(self, **kwargs):
         r"""Initialize MultiLayerPerceptron instance."""
-        warnings.filterwarnings(action="ignore", category=ChangedBehaviorWarning)
         warnings.filterwarnings(action="ignore", category=ConvergenceWarning)
         warnings.filterwarnings(action="ignore", category=DataConversionWarning)
         warnings.filterwarnings(action="ignore", category=DataDimensionalityWarning)
         warnings.filterwarnings(action="ignore", category=EfficiencyWarning)
         warnings.filterwarnings(action="ignore", category=FitFailedWarning)
-        warnings.filterwarnings(action="ignore", category=NonBLASDotWarning)
         warnings.filterwarnings(action="ignore", category=UndefinedMetricWarning)
 
         self._params = dict(

niaaml/classifiers/quadratic_driscriminant_analysis.py

@@ -3,13 +3,11 @@
 
 import warnings
 from sklearn.exceptions import (
-    ChangedBehaviorWarning,
     ConvergenceWarning,
     DataConversionWarning,
     DataDimensionalityWarning,
     EfficiencyWarning,
     FitFailedWarning,
-    NonBLASDotWarning,
     UndefinedMetricWarning,
 )
 
@@ -41,13 +39,11 @@ class QuadraticDiscriminantAnalysis(Classifier):
 
     def __init__(self, **kwargs):
         r"""Initialize QuadraticDiscriminantAnalysis instance."""
-        warnings.filterwarnings(action="ignore", category=ChangedBehaviorWarning)
         warnings.filterwarnings(action="ignore", category=ConvergenceWarning)
         warnings.filterwarnings(action="ignore", category=DataConversionWarning)
         warnings.filterwarnings(action="ignore", category=DataDimensionalityWarning)
         warnings.filterwarnings(action="ignore", category=EfficiencyWarning)
         warnings.filterwarnings(action="ignore", category=FitFailedWarning)
-        warnings.filterwarnings(action="ignore", category=NonBLASDotWarning)
         warnings.filterwarnings(action="ignore", category=UndefinedMetricWarning)
 
         self.__qda = QDA()

niaaml/classifiers/random_forest.py

@@ -6,13 +6,11 @@
 
 import warnings
 from sklearn.exceptions import (
-    ChangedBehaviorWarning,
     ConvergenceWarning,
     DataConversionWarning,
     DataDimensionalityWarning,
     EfficiencyWarning,
     FitFailedWarning,
-    NonBLASDotWarning,
     UndefinedMetricWarning,
 )
 
@@ -44,13 +42,11 @@ class RandomForest(Classifier):
 
     def __init__(self, **kwargs):
         r"""Initialize RandomForestClassifier instance."""
-        warnings.filterwarnings(action="ignore", category=ChangedBehaviorWarning)
         warnings.filterwarnings(action="ignore", category=ConvergenceWarning)
         warnings.filterwarnings(action="ignore", category=DataConversionWarning)
         warnings.filterwarnings(action="ignore", category=DataDimensionalityWarning)
         warnings.filterwarnings(action="ignore", category=EfficiencyWarning)
         warnings.filterwarnings(action="ignore", category=FitFailedWarning)
-        warnings.filterwarnings(action="ignore", category=NonBLASDotWarning)
         warnings.filterwarnings(action="ignore", category=UndefinedMetricWarning)
 
         self._params = dict(