tests: change data set loading according to deprecation warnings

andreArtelt · Aug 4, 2020 · f56a2ee · f56a2ee
1 parent e2502a2
commit f56a2ee
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Showing 8 changed files with 16 additions and 16 deletions.
diff --git a/tests/sklearn/test_sklearn_decisiontree.py b/tests/sklearn/test_sklearn_decisiontree.py
@@ -96,7 +96,7 @@ def test_plausible_counterfactual():
 
 def test_decisiontree_classifier():
     # Load data
-    X, y = load_iris(True)
+    X, y = load_iris(return_X_y=True)
 
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=4242)
 
@@ -124,7 +124,7 @@ def test_decisiontree_classifier():
 
 def test_decisiontree_regressor():
     # Load data
-    X, y = load_boston(True)
+    X, y = load_boston(return_X_y=True)
 
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=4242)
 

diff --git a/tests/sklearn/test_sklearn_knn.py b/tests/sklearn/test_sklearn_knn.py
@@ -14,7 +14,7 @@
 
 def test_knn_classifier():
     # Load data
-    X, y = load_iris(True)
+    X, y = load_iris(return_X_y=True)
 
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=4242)
 
@@ -70,7 +70,7 @@ def test_knn_classifier():
 
 def test_knn_regressor():
     # Load data
-    X, y = load_boston(True)
+    X, y = load_boston(return_X_y=True)
 
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=4242)
 

diff --git a/tests/sklearn/test_sklearn_lda.py b/tests/sklearn/test_sklearn_lda.py
@@ -15,7 +15,7 @@
 
 def test_lda():
     # Load data
-    X, y = load_iris(True)
+    X, y = load_iris(return_X_y=True)
 
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=4242)
 

diff --git a/tests/sklearn/test_sklearn_linearregression.py b/tests/sklearn/test_sklearn_linearregression.py
@@ -15,7 +15,7 @@
 
 def test_linearregression():
     # Load data
-    X, y = load_boston(True)
+    X, y = load_boston(return_X_y=True)
 
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=4242)
 

diff --git a/tests/sklearn/test_sklearn_lvq.py b/tests/sklearn/test_sklearn_lvq.py
@@ -16,7 +16,7 @@
 
 def test_glvq():
     # Load data
-    X, y = load_iris(True)
+    X, y = load_iris(return_X_y=True)
 
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=4242)
 
@@ -90,7 +90,7 @@ def test_glvq():
 
 def test_gmlvq():
     # Load data
-    X, y = load_iris(True)
+    X, y = load_iris(return_X_y=True)
 
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=4242)
 
@@ -160,7 +160,7 @@ def test_gmlvq():
 
 def test_lgmlvq():
     # Load data
-    X, y = load_iris(True)
+    X, y = load_iris(return_X_y=True)
 
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=4242)
 
@@ -230,7 +230,7 @@ def test_lgmlvq():
 
 def test_lgmlvq_classwise():
     # Load data
-    X, y = load_iris(True)
+    X, y = load_iris(return_X_y=True)
 
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=4242)
 

diff --git a/tests/sklearn/test_sklearn_naivebayes.py b/tests/sklearn/test_sklearn_naivebayes.py
@@ -15,7 +15,7 @@
 
 def test_gaussiannaivebayes():
     # Load data
-    X, y = load_iris(True)
+    X, y = load_iris(return_X_y=True)
 
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=4242)
 
@@ -91,7 +91,7 @@ def test_gaussiannaivebayes():
     assert all([True if i in features_whitelist else delta[i] == 0. for i in range(x_orig.shape[0])])
 
     # Test binary case
-    X, y = load_iris(True)
+    X, y = load_iris(return_X_y=True)
     idx = y != 2
     X, y = X[idx, :], y[idx]
 

diff --git a/tests/sklearn/test_sklearn_qda.py b/tests/sklearn/test_sklearn_qda.py
@@ -15,7 +15,7 @@
 
 def test_qda():
     # Load data
-    X, y = load_iris(True)
+    X, y = load_iris(return_X_y=True)
 
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=4242)
 
@@ -90,7 +90,7 @@ def test_qda():
     assert all([True if i in features_whitelist else delta[i] == 0. for i in range(x_orig.shape[0])])
 
     # Test binary case
-    X, y = load_iris(True)
+    X, y = load_iris(return_X_y=True)
     idx = y != 2
     X, y = X[idx, :], y[idx]
 

diff --git a/tests/sklearn/test_sklearn_randomforest.py b/tests/sklearn/test_sklearn_randomforest.py
@@ -14,7 +14,7 @@
 
 def test_randomforest_classifier():
     # Load data
-    X, y = load_iris(True)
+    X, y = load_iris(return_X_y=True)
 
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=4242)
 
@@ -52,7 +52,7 @@ def test_randomforest_classifier():
 
 def test_randomforest_regressor():
     # Load data
-    X, y = load_boston(True)
+    X, y = load_boston(return_X_y=True)
 
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=4242)