Updated calculation of accuracy

Author: joseph-hellerstein

src/iplane/model_runner.py

@@ -123,7 +123,10 @@ def plotEvaluate(self, test_loader: DataLoader, ax=None, is_plot: bool = True):
         prediction_tnsr = self.predict(feature_tnsr)
         prediction_df = pd.DataFrame(prediction_tnsr.to(cn.CPU).numpy(), columns=columns)
         target_df = pd.DataFrame(target_tnsr.to(cn.CPU).numpy(), columns=columns)
-        plot_df = (prediction_df - target_df)/target_df
+        numerator_arr = np.abs(prediction_df - target_df)/target_df
+        arr1 = numerator_arr/target_df.values
+        arr2 = numerator_arr/prediction_df.values
+        plot_df = pd.DataFrame(np.maximum(arr1, arr2), columns=columns)
         plot_df['class'] = "relative error"
         # Plot
         if ax is None:

tests/test_model_runner_nn.py

@@ -13,8 +13,8 @@
 
 IGNORE_TESTS = True
 IS_PLOT = True
+NUM_EPOCH = 1000
 NUM_EPOCH = 20000
-NUM_EPOCH = 2000
 
 TARGET_COLUMN = "target"  # Assuming the target column is named 'target'
 NUM_DEPENDENT_FEATURE = 6