Merge branch 'master' of github.com:lazyprogrammer/machine_learning_examples

Author: User

ann_logistic_extra/ann_train.py

@@ -77,7 +77,7 @@ def cross_entropy(T, pY):
 print("Final train classification_rate:", classification_rate(Ytrain, predict(pYtrain)))
 print("Final test classification_rate:", classification_rate(Ytest, predict(pYtest)))
 
-legend1, = plt.plot(train_costs, label='train cost')
-legend2, = plt.plot(test_costs, label='test cost')
-plt.legend([legend1, legend2])
+plt.plot(train_costs, label='train cost')
+plt.plot(test_costs, label='test cost')
+plt.legend()
 plt.show()

ann_logistic_extra/logistic_softmax_train.py

@@ -70,7 +70,7 @@ def cross_entropy(T, pY):
 print("Final train classification_rate:", classification_rate(Ytrain, predict(pYtrain)))
 print("Final test classification_rate:", classification_rate(Ytest, predict(pYtest)))
 
-legend1, = plt.plot(train_costs, label='train cost')
-legend2, = plt.plot(test_costs, label='test cost')
-plt.legend([legend1, legend2])
+plt.plot(train_costs, label='train cost')
+plt.plot(test_costs, label='test cost')
+plt.legend()
 plt.show()

ann_logistic_extra/logistic_train.py

@@ -55,9 +55,9 @@ def cross_entropy(T, pY):
 print("Final train classification_rate:", classification_rate(Ytrain, np.round(pYtrain)))
 print("Final test classification_rate:", classification_rate(Ytest, np.round(pYtest)))
 
-legend1, = plt.plot(train_costs, label='train cost')
-legend2, = plt.plot(test_costs, label='test cost')
-plt.legend([legend1, legend2])
+plt.plot(train_costs, label='train cost')
+plt.plot(test_costs, label='test cost')
+plt.legend()
 plt.show()