# HG changeset patch
# User Jeff Hammel <k0scist@gmail.com>
# Date 1504563569 25200
# Node ID 4d173452377ef56b9bbb14a54dfa4cadb1b9f9ad
# Parent  857a606783e1bc89c7071e931f479105d5be1e81
notes on backpropagation

diff -r 857a606783e1 -r 4d173452377e tvii/logistic_regression.py
--- a/tvii/logistic_regression.py	Mon Sep 04 15:06:38 2017 -0700
+++ b/tvii/logistic_regression.py	Mon Sep 04 15:19:29 2017 -0700
@@ -15,6 +15,11 @@
 from .sigmoid import sigmoid
 
 
+def loss(a, y):
+    # UNTESTED!
+    # derivative = -(y/a) + (1-y)/(1-a)
+    return -y*np.log(a) - (1-y)*np.log(1-a)
+
 def propagate(w, b, X, Y):
     """
     Implement the cost function and its gradient for the propagation: