Fixed: SVC Fixed and tested

Caparrini · Feb 23, 2024 · bd6e1c8 · bd6e1c8
1 parent 3e54c16
commit bd6e1c8
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Showing 2 changed files with 6 additions and 16 deletions.
diff --git a/mloptimizer/genoptimizer/svc.py b/mloptimizer/genoptimizer/svc.py
@@ -15,24 +15,14 @@ def get_default_hyperparams():
         default_hyperparams = {
             'C': Hyperparam("C", 1, 10000, float, 10),
             'degree': Hyperparam("degree", 0, 6, int),
-            'gamma': Hyperparam("gamma", 10, 100000000, float, 100)
+            'gamma': Hyperparam("gamma", 10, 100000000, float, 100),
+            'max_iter': Hyperparam("max_iter", 100, 1000, int)
         }
         return default_hyperparams
 
     def get_clf(self, individual):
         individual_dict = self.individual2dict(individual)
-        clf = SVC(C=individual_dict['C'],
-                  cache_size=8000000,
-                  class_weight="balanced",
-                  coef0=0.0,
-                  decision_function_shape='ovr',
-                  degree=individual_dict['degree'], gamma=individual_dict['gamma'],
-                  kernel='rbf',
-                  max_iter=100000,
-                  probability=False,
-                  random_state=None,
-                  shrinking=True,
-                  tol=0.001,
-                  verbose=False
+        clf = SVC(random_state=self.mlopt_seed,
+                  **individual_dict
                   )
         return clf
diff --git a/mloptimizer/test/test_genoptimizer/test_optimizers.py b/mloptimizer/test/test_genoptimizer/test_optimizers.py
@@ -20,7 +20,7 @@
                          (TreeOptimizer, ForestOptimizer,
                           ExtraTreesOptimizer, GradientBoostingOptimizer,
                           XGBClassifierOptimizer,
-                          # SVCOptimizer,
+                          SVCOptimizer,
                           KerasClassifierOptimizer))
 @pytest.mark.parametrize('dataset',
                          (load_breast_cancer, load_iris))
@@ -44,7 +44,7 @@ def test_get_subclasses():
 
 @pytest.mark.parametrize('optimizer',
                          (TreeOptimizer, ForestOptimizer,
-                          # ExtraTreesOptimizer, GradientBoostingOptimizer,
+                          ExtraTreesOptimizer, GradientBoostingOptimizer,
                           XGBClassifierOptimizer,
                           # SVCOptimizer,KerasClassifierOptimizer
                           ))