diff --git a/train_BayesByBackprop_MNIST.py b/train_BayesByBackprop_MNIST.py
index 874e674..5302b47 100644
--- a/train_BayesByBackprop_MNIST.py
+++ b/train_BayesByBackprop_MNIST.py
@@ -216,7 +216,7 @@
 plt.xlabel('epoch')
 plt.grid(b=True, which='major', color='k', linestyle='-')
 plt.grid(b=True, which='minor', color='k', linestyle='--')
-lgd = plt.legend(['test error', 'train error'], markerscale=marker, prop={'size': textsize, 'weight': 'normal'})
+lgd = plt.legend(['train error', 'test error'], markerscale=marker, prop={'size': textsize, 'weight': 'normal'})
 ax = plt.gca()
 plt.title('classification costs')
 for item in ([ax.title, ax.xaxis.label, ax.yaxis.label] +
diff --git a/train_BootrapEnsemble_MNIST.py b/train_BootrapEnsemble_MNIST.py
index e85fb0b..bde6681 100644
--- a/train_BootrapEnsemble_MNIST.py
+++ b/train_BootrapEnsemble_MNIST.py
@@ -207,7 +207,7 @@
     plt.xlabel('epoch')
     plt.grid(b=True, which='major', color='k', linestyle='-')
     plt.grid(b=True, which='minor', color='k', linestyle='--')
-    lgd = plt.legend(['test error', 'train error'], markerscale=marker, prop={'size': textsize, 'weight': 'normal'})
+    lgd = plt.legend(['train error', 'test error'], markerscale=marker, prop={'size': textsize, 'weight': 'normal'})
     ax = plt.gca()
     plt.title('classification costs')
     for item in ([ax.title, ax.xaxis.label, ax.yaxis.label] +
@@ -235,4 +235,4 @@
     plt.savefig(results_dir + '/err%d.png' % iii, bbox_extra_artists=(lgd,), box_inches='tight')
 
 
-save_object(weight_set_samples, models_dir+'/state_dicts.pkl')
\ No newline at end of file
+save_object(weight_set_samples, models_dir+'/state_dicts.pkl')