Create ml_utils/metric/regression_metric.py

src/utils/ml_utils/metric/regression_metric.py

@@ -0,0 +1,20 @@
+from src.entity.artifact_entity import RegressionMetricArtifact
+from src.exception.exception import DeliveryTimeException
+from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score
+import sys
+
+def get_regression_score(y_true, y_pred) ->RegressionMetricArtifact:
+    try:
+        model_r2_score=r2_score(y_true, y_pred)
+        model_mean_absolute_error= mean_absolute_error(y_true, y_pred)
+        model_mean_squared_error=mean_squared_error(y_true, y_pred)
+
+        regression_metric = RegressionMetricArtifact(
+            r2_score=model_r2_score,
+            mean_absolute_error=model_mean_absolute_error,
+            mean_squared_error=model_mean_squared_error
+        )
+        return regression_metric
+    
+    except Exception as e:
+        raise DeliveryTimeException(e, sys)