python - 如何在 python 中为在 tensorflow 中实现的模型创建混淆矩阵？

Question

我正在使用 TensorFlow 在 Python 中训练模型，但我想打印模型预测数据（预测与实际）的混淆矩阵。我怎样才能做到这一点？到目前为止，我的代码（不包括数据加载和预处理）如下：

from sklearn.preprocessing import LabelEncoder
Y = data.label
le = LabelEncoder()

Y = le.fit_transform(Y)


Y = Y.reshape(-1,1)

len(X)

sequences = list()
for line in X:
    # integer encode line
    encoded_seq = [char_index[char] for char in line]
    # store
    sequences.append(encoded_seq)



padded_inputs = tf.keras.preprocessing.sequence.pad_sequences(
    sequences, padding="pre")
print(padded_inputs)


ex = tf.keras.preprocessing.sequence.pad_sequences(sequences, padding="pre")
print(ex)


#And here is the train_test_split
X_train, X_test, y_train, y_test = train_test_split(padded_inputs, Y, test_size= 0.1, 
random_state = 0)

X_train

y_train = y_train.astype("int32")

y_train

X_train.shape

X_test

print(X_train.shape)
max_len = 19
max_words = 57

from tensorflow.keras.optimizers import RMSprop

def RNN():
    inputs = tf.keras.Input(name='inputs',shape=[max_len])
    layer = Embedding(max_words,19,input_length=max_len)(inputs)
    layer = LSTM(64)(layer)
    layer = Dense(256,name='FC1')(layer)
    layer = Activation('relu')(layer)
    layer = Dropout(0.5)(layer)
    layer = Dense(1,name='out_layer')(layer)
    layer = Activation('sigmoid')(layer)
    model = tf.keras.Model(inputs=inputs,outputs=layer)
    return model

model = RNN()
model.summary()
model.compile(loss='binary_crossentropy',optimizer=RMSprop(),metrics=['accuracy'])

num_epochs = 40
log_dir = "logs/fit/" + datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir, histogram_freq=1)
history=model.fit(X_train, y_train,batch_size=128, epochs= num_epochs, validation_split=0.2, 
callbacks=[tensorboard_callback], verbose=2)



accr = model.evaluate(X_test,y_test)


print('Test set\nLoss: {:0.3f}\nAccuracy: {:0.3f}'.format(accr[0],accr[1]))

yhat = model.predict(X_test)

我试过使用：tf.math.confusion_matrix(labels, predictions, num_classes=None, weights=None, dtype=tf.dtypes.int32,name=None，但我不知道如何正确使用它代码。

标签： pythontensorflowconfusion-matrix