Added: Simple test for SklearnOptimizer

mloptimizer/test/test_genoptimizer/test_meta.py

@@ -0,0 +1,20 @@
+import pytest
+from mloptimizer import SklearnOptimizer, Hyperparam
+from sklearn.tree import DecisionTreeClassifier
+from sklearn.datasets import load_iris
+
+default_hyperparams = {
+            "min_samples_split": Hyperparam("min_samples_split", 2, 50, int),
+            "min_samples_leaf": Hyperparam("min_samples_leaf", 1, 20, int),
+            "max_depth": Hyperparam("max_depth", 2, 20, int),
+            "min_impurity_decrease": Hyperparam("min_impurity_decrease", 0, 150, float, 1000),
+            "ccp_alpha": Hyperparam("ccp_alpha", 0, 300, float, 100000)
+        }
+
+
+def test_mloptimizer():
+    X, y = load_iris(return_X_y=True)
+    mlopt = SklearnOptimizer(clf_class=DecisionTreeClassifier, custom_hyperparams=default_hyperparams,
+                             features=X, labels=y)
+    mlopt.optimize_clf(5, 5)
+    assert mlopt is not None