如何在CNN中建立混淆矩阵？

Question

我正在处理图像数据集，并且想从我的CNN模型构建混淆矩阵，我该怎么办？

model.fit({'input': X}, {'targets': Y}, n_epoch = 5, 
    validation_set =({'input': test_x}, {'targets': test_y}), 
    snapshot_step = 500, show_metric = True, run_id = MODEL_NAME) 
model.save(MODEL_NAME) 


'''Testing the data'''
 import matplotlib.pyplot as plt 
 # if you need to create the data: 
# test_data = process_test_data() 
# if you already have some saved: 
test_data = np.load('test_data.npy') 

fig = plt.figure() 

    for num, data in enumerate(test_data[:20]): 


    img_num = data[1] 
    img_data = data[0] 

    y = fig.add_subplot(4, 5, num + 1) 
    orig = img_data 
    data = img_data.reshape(IMG_SIZE, IMG_SIZE, 1) 

    # model_out = model.predict([data])[0] 
    model_out = model.predict([data])[0] 

    if np.argmax(model_out) == 1: str_label ='Cancer'
    else: str_label ='Normal'

    y.imshow(orig, cmap ='gray') 
    plt.title(str_label) 
    y.axes.get_xaxis().set_visible(False) 
    y.axes.get_yaxis().set_visible(False) 
plt.show() 
model_out = model.predict([data])[0] 
print(model_out)

如何在我的CNN中为测试和训练集创建厘米