added catch22regressor

aeon/testing/expected_results/expected_regressor_outputs.py

@@ -38,3 +38,33 @@
         0.4744,
     ]
 )
+
+covid_3month_preds["Catch22Regressor"] = np.array(
+    [
+        0.0302,
+        0.0354,
+        0.0352,
+        0.0345,
+        0.0259,
+        0.0484,
+        0.0369,
+        0.0827,
+        0.0737,
+        0.0526,
+    ]
+)
+
+cardano_sentiment_preds["Catch22Regressor"] = np.array(
+    [
+        0.2174,
+        0.1394,
+        0.3623,
+        0.1496,
+        0.3502,
+        0.2719,
+        0.1378,
+        0.076,
+        0.0587,
+        0.3773,
+    ]
+)

aeon/testing/expected_results/regressor_results_reproduction.py

@@ -4,7 +4,7 @@
 from sklearn.utils._testing import set_random_state
 
 from aeon.datasets import load_cardano_sentiment, load_covid_3month
-from aeon.regression.feature_based import FreshPRINCERegressor
+from aeon.regression.feature_based import FreshPRINCERegressor, Catch22Regressor
 
 
 def _reproduce_regression_covid_3month(estimator):
@@ -42,9 +42,13 @@ def _print_results_for_regressor(regressor_name, dataset_name):
         regressor = FreshPRINCERegressor.create_test_instance(
             parameter_set="results_comparison"
         )
+    elif regressor_name == "Catch22Regressor":
+        regressor = Catch22Regressor.create_test_instance(
+            parameter_set="results_comparison"
+        )
     else:
         raise ValueError(f"Unknown regressor: {regressor_name}")
-
+        
     if dataset_name == "Covid3Month":
         data_function = _reproduce_regression_covid_3month
     elif dataset_name == "CardanoSentiment":
@@ -62,4 +66,4 @@ def _print_results_for_regressor(regressor_name, dataset_name):
 
 if __name__ == "__main__":
     # change as required when adding new classifiers, datasets or updating results
-    _print_results_for_regressor("FreshPRINCERegressor", "Covid3Month")
+    _print_results_for_regressor("Catch22Regressor", "CardanoSentiment")