accuracy_test, correct_test=sess.run([accuracy, correct_prediction], feed_dict={x: test_set, t: target_test})
accuracy_train, correct_train=sess.run([accuracy, correct_prediction], feed_dict={x: train_set, t: target_train})
print('Train accuracy: %.2f%%' %(accuracy_train*100))
print('Test accuracy: %.2f%%' %(accuracy_test*100))
sensitivity_train=np.sum(correct_train*(target_train==1))/np.sum(target_train)
sensitivity_test=np.sum(correct_test*(target_test==1))/np.sum(target_test)
specificity_train=np.sum(correct_train*(target_train==0))/(len(target_train)-np.sum(target_train))
specificity_test=np.sum(correct_test*(target_test==0))/(len(target_test)-np.sum(target_test))