使用CNN训练的神经网络(CNN)进行以下精度测试：for root, dirs, files in os.walk(test_directory):
for file in files:
img = cv2.imread(root + '/' + file)
img = cv2.resize(img,(512,512),interpolation=cv2.INTER_AREA)
img = np.expand_dims(img, axis=0)
img = img/255.0
if os.path.basename(root) == 'nevus':
label = 1
elif os.path.basename(root) == 'melanoma':
label = 0
img_class = model.predict_classes(img)
prediction = img_class[0]
if prediction == label:
correct_classification = correct_classification + 1
print 'This is the prediction: '
print prediction
number_of_test_images = number_of_test_images + 1
print 'correct results:'
print correct_classification
print 'number of test images'
print number_of_test_images
print 'Accuray:'
print number_of_test_images/correct_classification * 100
有没有一种方法可以通过在测试数据集上测试模型来找到ROC曲线？在
谢谢。在
)
