diff --git a/precise/functions.py b/precise/functions.py
index 44daa8b..2655353 100644
--- a/precise/functions.py
+++ b/precise/functions.py
@@ -13,6 +13,8 @@
 # limitations under the License.
 from typing import *
 
+LOSS_BIAS = 0.9  # [0..1] where 1 is inf bias
+
 
 def weighted_log_loss(yt, yp) -> Any:
     """
@@ -21,23 +23,21 @@ def weighted_log_loss(yt, yp) -> Any:
     yp: Prediction
     """
     from keras import backend as K
-    weight = 0.7  # [0..1] where 1 is inf bias
 
     pos_loss = -(0 + yt) * K.log(0 + yp + K.epsilon())
     neg_loss = -(1 - yt) * K.log(1 - yp + K.epsilon())
 
-    return weight * K.mean(neg_loss) + (1. - weight) * K.mean(pos_loss)
+    return LOSS_BIAS * K.mean(neg_loss) + (1. - LOSS_BIAS) * K.mean(pos_loss)
 
 
 def weighted_mse_loss(yt, yp) -> Any:
     from keras import backend as K
-    weight = 0.9  # [0..1] where 1 is inf bias
 
     total = K.sum(K.ones_like(yt))
     neg_loss = total * K.sum(K.square(yp * (1 - yt))) / K.sum(1 - yt)
     pos_loss = total * K.sum(K.square(1. - (yp * yt))) / K.sum(yt)
 
-    return weight * neg_loss + (1. - weight) * pos_loss
+    return LOSS_BIAS * neg_loss + (1. - LOSS_BIAS) * pos_loss
 
 
 def false_pos(yt, yp) -> Any: