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src/utils.py

@@ -0,0 +1,27 @@
+from joblib import dump, load
+
+
+class LoadClassifierThreshold:
+    def __init__(self, model_path, threshold_path):
+        try:
+            self.model = load(model_path)
+        except Exception as e:
+            raise ValueError(f"Failed to load model from {model_path}: {str(e)}")
+
+        try:
+            with open(threshold_path, "r") as threshold_file:
+                self.threshold = float(threshold_file.read())
+        except Exception as e:
+            raise ValueError(f"Failed to load threshold from {threshold_path}: {str(e)}")
+
+    def predict_with_threshold(self, testset):
+        if not hasattr(self, 'model') or not hasattr(self, 'threshold'):
+            raise ValueError("Model or threshold not loaded correctly.")
+
+        try:
+            # Use the predicted probabilities and compare with the threshold
+            predicted_probabilities = self.model.predict_proba(testset)[:, 1]
+            predictions = (predicted_probabilities >= self.threshold).astype(int)
+            return predictions
+        except Exception as e:
+            raise ValueError(f"Prediction failed: {str(e)}")