diff --git a/modules/deeplearning/cnn_cld_frac.py b/modules/deeplearning/cnn_cld_frac.py
index 05bcae257acd8845f23e55f6194d08e57566e6b6..5c885ee4dfbb2d466240af3b56ce3efa1555ca96 100644
--- a/modules/deeplearning/cnn_cld_frac.py
+++ b/modules/deeplearning/cnn_cld_frac.py
@@ -226,14 +226,34 @@ def get_grid_cell_mean(grd_k):
 #     return s_t
 
 
+# def get_label_data(grd_k):
+#     grd_k = np.where(np.isnan(grd_k), 0, grd_k)
+#     cat_0 = np.logical_and(grd_k >= 0.0, grd_k < 0.15)
+#     cat_1 = np.logical_and(grd_k >= 0.15, grd_k < 0.85)
+#     cat_2 = np.logical_and(grd_k >= 0.85, grd_k <= 1.0)
+#     grd_k[cat_0] = -1
+#     grd_k[cat_1] = 0
+#     grd_k[cat_2] = 1
+#
+#     a = grd_k[:, 0::2, 0::2]
+#     b = grd_k[:, 1::2, 0::2]
+#     c = grd_k[:, 0::2, 1::2]
+#     d = grd_k[:, 1::2, 1::2]
+#     s = a + b + c + d
+#
+#     cat_0 = s <= -3
+#     cat_1 = np.logical_and(s > -3, s < 2)
+#     cat_2 = s >= 2
+#     s[cat_0] = 0
+#     s[cat_1] = 1
+#     s[cat_2] = 2
+#
+#     return s
+
+
 def get_label_data(grd_k):
     grd_k = np.where(np.isnan(grd_k), 0, grd_k)
-    cat_0 = np.logical_and(grd_k >= 0.0, grd_k < 0.15)
-    cat_1 = np.logical_and(grd_k >= 0.15, grd_k < 0.85)
-    cat_2 = np.logical_and(grd_k >= 0.85, grd_k <= 1.0)
-    grd_k[cat_0] = -1
-    grd_k[cat_1] = 0
-    grd_k[cat_2] = 1
+    grd_k = np.where(grd_k < 0.50, 0, 1)
 
     a = grd_k[:, 0::2, 0::2]
     b = grd_k[:, 1::2, 0::2]
@@ -241,9 +261,9 @@ def get_label_data(grd_k):
     d = grd_k[:, 1::2, 1::2]
     s = a + b + c + d
 
-    cat_0 = s <= -3
-    cat_1 = np.logical_and(s > -3, s < 2)
-    cat_2 = s >= 2
+    cat_0 = (s == 0)
+    cat_1 = np.logical_and(s > 0, s < 4)
+    cat_2 = (s == 4)
     s[cat_0] = 0
     s[cat_1] = 1
     s[cat_2] = 2