Updates sklearn to v1.0.0 (#1217)

DistrictDataLabs · Feb 18, 2022 · df45161 · df45161
1 parent 20acdcc
commit df45161
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Showing 34 changed files with 19 additions and 19 deletions.
diff --git a/docs/requirements.txt b/docs/requirements.txt
@@ -1,7 +1,7 @@
 # Library Dependencies
 matplotlib>=3.3
 scipy>=1.6.0
-scikit-learn>=0.24
+scikit-learn>=1.0.0
 numpy>=1.16.0
 cycler>=0.10.0
 

diff --git a/requirements.txt b/requirements.txt
@@ -1,7 +1,7 @@
 ## Dependencies
 matplotlib>=2.0.2,!=3.0.0
 scipy>=1.0.0
-scikit-learn>=0.20
+scikit-learn>=1.0.0
 numpy>=1.16.0
 cycler>=0.10.0
 

diff --git a/..._images/test_classifier/test_threshold/test_binary_discrimination_threshold.png b/..._images/test_classifier/test_threshold/test_binary_discrimination_threshold.png
diff --git a/tests/baseline_images/test_classifier/test_threshold/test_quick_method.png b/tests/baseline_images/test_classifier/test_threshold/test_quick_method.png
diff --git a/tests/baseline_images/test_cluster/test_elbow/test_integrated_kmeans_elbow.png b/tests/baseline_images/test_cluster/test_elbow/test_integrated_kmeans_elbow.png
diff --git a/...line_images/test_cluster/test_elbow/test_integrated_mini_batch_kmeans_elbow.png b/...line_images/test_cluster/test_elbow/test_integrated_mini_batch_kmeans_elbow.png
diff --git a/tests/baseline_images/test_cluster/test_elbow/test_quick_method.png b/tests/baseline_images/test_cluster/test_elbow/test_quick_method.png
diff --git a/tests/baseline_images/test_cluster/test_icdm/test_quick_method.png b/tests/baseline_images/test_cluster/test_icdm/test_quick_method.png
diff --git a/...line_images/test_cluster/test_silhouette/test_colormap_as_colors_silhouette.png b/...line_images/test_cluster/test_silhouette/test_colormap_as_colors_silhouette.png
diff --git a/tests/baseline_images/test_cluster/test_silhouette/test_colormap_silhouette.png b/tests/baseline_images/test_cluster/test_silhouette/test_colormap_silhouette.png
diff --git a/tests/baseline_images/test_cluster/test_silhouette/test_colors_silhouette.png b/tests/baseline_images/test_cluster/test_silhouette/test_colors_silhouette.png
diff --git a/...s/test_cluster/test_silhouette/test_integrated_mini_batch_kmeans_silhouette.png b/...s/test_cluster/test_silhouette/test_integrated_mini_batch_kmeans_silhouette.png
diff --git a/tests/baseline_images/test_cluster/test_silhouette/test_quick_method.png b/tests/baseline_images/test_cluster/test_silhouette/test_quick_method.png
diff --git a/...es/test_features/test_manifold/test_manifold_quick_method_continuous_target.png b/...es/test_features/test_manifold/test_manifold_quick_method_continuous_target.png
diff --git a/tests/baseline_images/test_features/test_manifold/test_manifold_regression.png b/tests/baseline_images/test_features/test_manifold/test_manifold_regression.png
diff --git a/tests/baseline_images/test_features/test_manifold/test_manifold_regression_3d.png b/tests/baseline_images/test_features/test_manifold/test_manifold_regression_3d.png
diff --git a/tests/baseline_images/test_meta/test_random_visualizer_not_close.png b/tests/baseline_images/test_meta/test_random_visualizer_not_close.png
diff --git a/tests/baseline_images/test_model_selection/test_importances/test_topn.png b/tests/baseline_images/test_model_selection/test_importances/test_topn.png
diff --git a/tests/baseline_images/test_model_selection/test_importances/test_topn_negative.png b/tests/baseline_images/test_model_selection/test_importances/test_topn_negative.png
diff --git a/tests/baseline_images/test_model_selection/test_learning_curve/test_clusters.png b/tests/baseline_images/test_model_selection/test_learning_curve/test_clusters.png
diff --git a/.../baseline_images/test_regressor/test_prediction_error/test_prediction_error.png b/.../baseline_images/test_regressor/test_prediction_error/test_prediction_error.png
diff --git a/tests/baseline_images/test_text/test_tsne/test_integrated_tsne.png b/tests/baseline_images/test_text/test_tsne/test_integrated_tsne.png
diff --git a/tests/baseline_images/test_text/test_tsne/test_make_classification_tsne.png b/tests/baseline_images/test_text/test_tsne/test_make_classification_tsne.png
diff --git a/...eline_images/test_text/test_tsne/test_make_classification_tsne_class_labels.png b/...eline_images/test_text/test_tsne/test_make_classification_tsne_class_labels.png
diff --git a/tests/baseline_images/test_text/test_tsne/test_no_target_tsne.png b/tests/baseline_images/test_text/test_tsne/test_no_target_tsne.png
diff --git a/tests/baseline_images/test_text/test_tsne/test_quick_method.png b/tests/baseline_images/test_text/test_tsne/test_quick_method.png
diff --git a/tests/baseline_images/test_text/test_tsne/test_visualizer_with_pandas.png b/tests/baseline_images/test_text/test_tsne/test_visualizer_with_pandas.png
diff --git a/tests/rand.py b/tests/rand.py
@@ -73,7 +73,7 @@ def generate(self):
             Center/blob each point belongs to (used for color)
         """
         return make_blobs(
-            self.n_samples, 2, self.n_blobs, random_state=self.random_state
+            n_samples=self.n_samples, n_features=2, centers=self.n_blobs, random_state=self.random_state
         )
 
     def fit(self, *args, **kwargs):

diff --git a/tests/requirements.txt b/tests/requirements.txt
@@ -6,7 +6,7 @@
 # Library Dependencies
 matplotlib==3.4.2
 scipy==1.7.0
-scikit-learn==0.24.2
+scikit-learn==1.0.0
 numpy==1.21.0
 cycler==0.10.0
 
@@ -25,4 +25,4 @@ umap-learn==0.5.1
 
 # Third-Party Estimator Tests
 # xgboost==1.2.0
-# catboost==0.24.1
+# catboost==0.24.1
diff --git a/tests/test_base.py b/tests/test_base.py
@@ -318,7 +318,7 @@ def test_draw_visualizer_grid(self):
         # show is required here (do not replace with finalize)!
         assert grid.show() is not None
 
-        self.assert_images_similar(grid)
+        self.assert_images_similar(grid, tol=1.0)
 
     @pytest.mark.xfail(
         IS_WINDOWS_OR_CONDA,
@@ -340,7 +340,7 @@ def test_draw_with_rows(self):
         # show is required here (do not replace with finalize)!
         assert grid.show() is not None
 
-        self.assert_images_similar(grid)
+        self.assert_images_similar(grid, tol=1.0)
 
     @pytest.mark.xfail(
         IS_WINDOWS_OR_CONDA,
@@ -362,7 +362,7 @@ def test_draw_with_cols(self):
         # show is required here (do not replace with finalize)!
         assert grid.show() is not None
 
-        self.assert_images_similar(grid)
+        self.assert_images_similar(grid, tol=1.0)
 
     def test_cant_define_both_rows_cols(self):
         """

diff --git a/tests/test_classifier/test_threshold.py b/tests/test_classifier/test_threshold.py
@@ -71,7 +71,7 @@ def test_binary_discrimination_threshold(self):
 
         _, ax = plt.subplots()
 
-        model = BernoulliNB(3)
+        model = BernoulliNB()
         visualizer = DiscriminationThreshold(model, ax=ax, random_state=23)
 
         visualizer.fit(X, y)
@@ -161,7 +161,7 @@ def test_quick_method(self):
 
         _, ax = plt.subplots()
 
-        discrimination_threshold(BernoulliNB(3), X, y, ax=ax, random_state=5, show=False)
+        discrimination_threshold(BernoulliNB(), X, y, ax=ax, random_state=5, show=False)
         self.assert_images_similar(ax=ax, tol=10)
 
     @patch.object(DiscriminationThreshold, "draw", autospec=True)
@@ -232,7 +232,7 @@ def test_threshold_default_initialization(self):
         """
         Test initialization default parameters
         """
-        model = BernoulliNB(3)
+        model = BernoulliNB()
         viz = DiscriminationThreshold(model)
         assert viz.estimator is model
         assert viz.color is None

diff --git a/tests/test_cluster/test_icdm.py b/tests/test_cluster/test_icdm.py
@@ -270,7 +270,7 @@ def test_legend_matplotlib_version(self, mock_toolkit):
         """
         ValueError is raised when matplotlib version is incorrect and legend=True
         """
-        with pytst.raises(ImportError):
+        with pytest.raises(ImportError):
             from mpl_toolkits.axes_grid1 import inset_locator
 
             assert not inset_locator

diff --git a/tests/test_meta.py b/tests/test_meta.py
@@ -117,7 +117,7 @@ def test_image_comparison_not_in_assertion(self):
 
     def test_missing_baseline_image(self):
         """
-        Test that a missing basline image raises an exception
+        Test that a missing baseline image raises an exception
         """
         viz = RandomVisualizer(random_state=14).fit()
         viz.finalize()
@@ -154,7 +154,7 @@ def test_random_visualizer_not_close(self):
         """
         # Baseline image random_state=224
         # NOTE: if regenerating baseline images, skip this one or change random state!
-        viz = RandomVisualizer(random_state=225).fit()
+        viz = RandomVisualizer(random_state=224).fit()
         viz.finalize()
 
         with pytest.raises(ImageComparisonFailure, match="images not close"):

diff --git a/tests/test_model_selection/test_importances.py b/tests/test_model_selection/test_importances.py
@@ -228,7 +228,7 @@ def test_multi_coefs_stacked(self):
         """
         Test stack plot with multidimensional coefficients
         """
-        X, y = load_iris(True)
+        X, y = load_iris(return_X_y=True)
 
         viz = FeatureImportances(
             LogisticRegression(solver="liblinear", random_state=222), stack=True
@@ -455,7 +455,7 @@ def test_topn_stacked(self):
         Test stack plot with only the three most important features by sum of
         each feature's importance across all classes
         """
-        X, y = load_iris(True)
+        X, y = load_iris(return_X_y=True)
 
         viz = FeatureImportances(
             LogisticRegression(solver="liblinear", random_state=222),
@@ -473,7 +473,7 @@ def test_topn_negative_stacked(self):
         Test stack plot with only the three least important features by sum of
         each feature's importance across all classes
         """
-        X, y = load_iris(True)
+        X, y = load_iris(return_X_y=True)
 
         viz = FeatureImportances(
             LogisticRegression(solver="liblinear", random_state=222),
@@ -490,7 +490,7 @@ def test_topn(self):
         """
         Test plot with only top three important features by absolute value
         """
-        X, y = load_iris(True)
+        X, y = load_iris(return_X_y=True)
 
         viz = FeatureImportances(
             GradientBoostingClassifier(random_state=42), topn=3
@@ -505,7 +505,7 @@ def test_topn_negative(self):
         """
         Test plot with only the three least important features by absolute value
         """
-        X, y = load_iris(True)
+        X, y = load_iris(return_X_y=True)
 
         viz = FeatureImportances(
             GradientBoostingClassifier(random_state=42), topn=-3