feat: warn user with clear message when test labels empty

freqtrade/freqai/base_models/BaseRegressionModel.py

@@ -6,6 +6,7 @@ import numpy as np
 import numpy.typing as npt
 from pandas import DataFrame
 
+from freqtrade.exceptions import DependencyException
 from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
 from freqtrade.freqai.freqai_interface import IFreqaiModel
 
@@ -63,12 +64,19 @@ class BaseRegressionModel(IFreqaiModel):
         dd["train_labels"], _, _ = dk.label_pipeline.fit_transform(dd["train_labels"])
 
         if self.freqai_info.get("data_split_parameters", {}).get("test_size", 0.1) != 0:
-            (dd["test_features"], dd["test_labels"], dd["test_weights"]) = (
-                dk.feature_pipeline.transform(
-                    dd["test_features"], dd["test_labels"], dd["test_weights"]
+            if dd["test_labels"].shape[0] == 0:
+                raise DependencyException(
+                    f"{pair}: test set is empty after filtering. "
+                    f"This is usually caused by overly strict SVM thresholds or insufficient data. "
+                    f"Try reducing 'test_size' or relaxing your SVM conditions."
                 )
-            )
-            dd["test_labels"], _, _ = dk.label_pipeline.transform(dd["test_labels"])
+            else:
+                (dd["test_features"], dd["test_labels"], dd["test_weights"]) = (
+                    dk.feature_pipeline.transform(
+                        dd["test_features"], dd["test_labels"], dd["test_weights"]
+                    )
+                )
+                dd["test_labels"], _, _ = dk.label_pipeline.transform(dd["test_labels"])
 
         logger.info(
             f"Training model on {len(dk.data_dictionary['train_features'].columns)} features"