diff --git a/examples/example.ini b/examples/example.ini
index c1f9edcc..cac0a5be 100644
--- a/examples/example.ini
+++ b/examples/example.ini
@@ -78,7 +78,7 @@ q_max = 90
 # Training data file
 training_image = /home/ceholden/Documents/yatsm/examples/training_data.gtif
 # Training data masked values
-mask_values = 0,255
+roi_mask_values = 0,255
 # Date range
 training_start = 1999-01-01
 training_end = 2001-01-01
diff --git a/examples/p035r032_example.ini b/examples/p035r032_example.ini
index 997e69cf..6688dffe 100644
--- a/examples/p035r032_example.ini
+++ b/examples/p035r032_example.ini
@@ -78,7 +78,7 @@ q_max = 90
 # Training data file
 training_image =
 # Training data masked values
-mask_values = 0,255
+roi_mask_values = 0,255
 # Date range
 training_start = 1999-01-01
 training_end = 2001-01-01
diff --git a/scripts/train_yatsm.py b/scripts/train_yatsm.py
index d4a63ca0..5d2be3f6 100755
--- a/scripts/train_yatsm.py
+++ b/scripts/train_yatsm.py
@@ -128,7 +128,7 @@ def get_training_inputs(dataset_config, exit_on_missing=False):
         raise
 
     # Loop through samples in ROI extracting features
-    mask = ~np.in1d(roi, dataset_config['mask_values']).reshape(roi.shape)
+    mask = ~np.in1d(roi, dataset_config['roi_mask_values']).reshape(roi.shape)
     row, col = np.where(mask)
     y = roi[row, col]
 
diff --git a/yatsm/config_parser.py b/yatsm/config_parser.py
index 2e0198d8..fb54907b 100644
--- a/yatsm/config_parser.py
+++ b/yatsm/config_parser.py
@@ -30,7 +30,7 @@ def parse_config_v0_1_x(config_file):
 robust = false
 [classification]
 training_image = None
-mask_values = 0, 255
+roi_mask_values = 0, 255
 cache_training =
     """
 
@@ -57,12 +57,12 @@ def parse_config_v0_1_x(config_file):
     if config.has_section('classification'):
         dataset_config['training_image'] = config.get('classification',
                                                       'training_image')
-        dataset_config['mask_values'] = config.get('classification',
-                                                   'mask_values')
-        if dataset_config['mask_values']:
-            dataset_config['mask_values'] = np.array([
+        dataset_config['roi_mask_values'] = config.get('classification',
+                                                   'roi_mask_values')
+        if dataset_config['roi_mask_values']:
+            dataset_config['roi_mask_values'] = np.array([
                 int(v) for v in
-                dataset_config['mask_values'].replace(' ', ',').split(',')
+                dataset_config['roi_mask_values'].replace(' ', ',').split(',')
                 if v != ','])
         dataset_config['cache_training'] = config.get(
             'classification', 'cache_training')