fix: train valid purged ML artifacts

tests/test_ml_optimizer_validation.py

@@ -1,5 +1,7 @@
 from datetime import datetime, timedelta
 
+import numpy as np
+
 from ml import optimizer
 
 
@@ -72,3 +74,16 @@ def test_run_out_of_sample_comparison_scores_only_validation_rows_with_fold_weig
 
     caution_equal = next(bucket for bucket in comparison["equal_weight"] if bucket["label"] == "CAUTION — OVERHEATED")
     assert caution_equal["days"] == 2
+
+
+def test_classification_splits_skip_training_windows_with_one_class():
+    y = np.array([1, 1, 1, 0, 1, 0])
+    splits = [
+        (np.array([0, 1]), np.array([2, 3])),
+        (np.array([0, 1, 3, 4]), np.array([5])),
+    ]
+
+    viable = list(optimizer.viable_classification_splits(y, splits))
+
+    assert len(viable) == 1
+    assert viable[0][0].tolist() == [0, 1, 3, 4]