update

Author: User

ann_logistic_extra/ann_train.py

@@ -48,8 +48,8 @@ def predict(P_Y_given_X):
 def classification_rate(Y, P):
     return np.mean(Y == P)
 
-def cross_entropy(T, pY):
-    return -np.mean(T*np.log(pY))
+def cross_entropy(Y, pY):
+    return -np.sum(Y * np.log(pY)) / len(T)
 
 
 # train loop

ann_logistic_extra/logistic_softmax_train.py

@@ -44,8 +44,8 @@ def predict(P_Y_given_X):
 def classification_rate(Y, P):
     return np.mean(Y == P)
 
-def cross_entropy(T, pY):
-    return -np.mean(T*np.log(pY))
+def cross_entropy(Y, pY):
+    return -np.sum(Y * np.log(pY)) / len(Y)
 
 
 # train loop

ann_logistic_extra/process.py

@@ -21,7 +21,7 @@ def get_data():
   # df.head()
 
   # easier to work with numpy array
-  data = df.values
+  data = df.to_numpy()
 
   # shuffle it
   np.random.shuffle(data)