feat(ml): add classification report generation to model evaluation to show all metrics during training

code/src/ml/model_selection.py

@@ -2,7 +2,7 @@ import numpy as np
 import pandas as pd
 import os
 import matplotlib.pyplot as plt
-from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay
+from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay, classification_report
 from joblib import load
 
 def create_ready_data(
@@ -159,6 +159,7 @@ def train_and_evaluate_model(
                 # Continue despite export error
 
         result["success"] = True
+        result["classification_report"] = classification_report(y_test, y_pred, output_dict=True)
         return result
 
     except Exception as e: