Upload app_revised_with_r_value.py

app_revised_with_r_value.py

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+# Replace this function in your utils or metric section
+def r_value(y_true, y_pred):
+    y_true = np.asarray(y_true)
+    y_pred = np.asarray(y_pred)
+    mask = np.isfinite(y_true) & np.isfinite(y_pred)
+    return float(np.corrcoef(y_true[mask], y_pred[mask])[0, 1])
+
+# Replace your metrics assignment for train/test/validate like this:
+# Old:
+# "R2": r2_score(...)
+# New:
+"R": r_value(...)
+
+# In all metric displays like:
+# c1.metric("R²", f"{m['R2']:.4f}")
+# Change to:
+c1.metric("R", f"{m['R']:.2f}")
+
+# In all metric panels for Train, Test, Validate
+c1.metric("R", f"{m['R']:.2f}")
+c2.metric("RMSE", f"{m['RMSE']:.2f}")
+c3.metric("MAE", f"{m['MAE']:.2f}")
+
+# Also replace in the 'Validation' and 'Prediction' sections accordingly.
+# Ensure all table metrics and summary stats (pred_min, pred_max, etc.) use 2 decimal digits:
+f"{value:.2f}"