v0.1.0

test/test_split.py

@@ -0,0 +1,45 @@
+import unittest
+
+from sklearn.datasets import fetch_openml
+from flaml.automl import AutoML
+from sklearn.model_selection import train_test_split
+from sklearn.metrics import accuracy_score
+
+
+dataset = "Airlines"
+
+
+def _test(split_type):
+    automl = AutoML()
+
+    automl_settings = {
+        "time_budget": 2,
+        # "metric": 'accuracy',
+        "task": 'classification',
+        "log_file_name": "test/{}.log".format(dataset),
+        "model_history": True,
+        "log_training_metric": True,
+        "split_type": split_type,
+    }
+
+    X, y = fetch_openml(name=dataset, return_X_y=True)
+    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33,
+     random_state=42)
+    automl.fit(X_train=X_train, y_train=y_train, **automl_settings)
+
+    pred = automl.predict(X_test)
+    acc = accuracy_score(y_test, pred)
+
+    print(acc)
+
+
+def test_stratified():
+    _test(split_type="stratified")
+
+
+def test_uniform():
+    _test(split_type="uniform")
+
+
+if __name__ == "__main__":
+    unittest.main()