[MINOR] Update function signatures in unsupervised mapper

losmib · Dec 6, 2021 · f2d7641 · f2d7641
1 parent 3bff2b1
commit f2d7641
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Showing 2 changed files with 8 additions and 8 deletions.
diff --git a/scripts/staging/sklearn/mappers/unsupervised.py b/scripts/staging/sklearn/mappers/unsupervised.py
@@ -76,8 +76,10 @@ def map_params(self):
         self.mapped_params = [
             self.params.get('n_components', 3),
             f'"{self.model_map.get(self.params.get("covariance_type", "VVV"))}"',
-            self.params.get('init_params', '"kmeans"'),
+            f'"{self.params.get("init_params", "kmeans")}"',
             self.params.get('max_iter', 100),
             self.params.get('reg_covar', 1e-6),
-            self.params.get('tol', 0.000001)
+            self.params.get('tol', 0.000001),
+            self.params.get('seed', -1),
+            self.params.get('verbose', 'FALSE')
         ]
diff --git a/scripts/staging/sklearn/run_tests.py b/scripts/staging/sklearn/run_tests.py
@@ -71,16 +71,14 @@ def test_valid(name, pipeline):
         make_pipeline(Normalizer(), TweedieRegressor()),
         make_pipeline(StandardScaler(), LogisticRegression()),
         make_pipeline(Normalizer(), LogisticRegression()),
-        #TODO: Tests which use PCA or DBSCAN, trigger a NullPointerException during parsing for some reason
         make_pipeline(StandardScaler(), DBSCAN()),
         make_pipeline(Normalizer(), DBSCAN()),
-        # make_pipeline(SimpleImputer(strategy='mean'), DBSCAN()),
-        # make_pipeline(SimpleImputer(strategy='median'), DBSCAN()),
+        make_pipeline(SimpleImputer(strategy='mean'), DBSCAN()),
+        make_pipeline(SimpleImputer(strategy='median'), DBSCAN()),
         make_pipeline(PCA(), KMeans()),
         make_pipeline(PCA(), DBSCAN()),
-        # TODO: GaussianMixtureModel results in LanguageException -- ERROR: [line 0:0] -- Function get_sample_maps() is undefined.
-        # make_pipeline(StandardScaler(), GaussianMixture()),
-        # make_pipeline(Normalizer(), GaussianMixture())
+        make_pipeline(StandardScaler(), GaussianMixture()),
+        make_pipeline(Normalizer(), GaussianMixture())
     ]
 
     valid_results = []