Machine learning 如何使用joblib保存神经网络模型

我试图用joblib将我的神经网络模型保存在熊猫中，因为它给了我96%的准确率。我的数据集有9列——预测乳腺癌的特征

y_train_categorical = to_categorical(y_train)
y_test_categorical = to_categorical(y_test)

from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense

neural_model = Sequential()
neural_model.add(Dense(units=6, activation='relu', input_dim=9))
neural_model.add(Dense(units=2, activation='softmax')) 

neural_model.compile(optimizer='adam',
              loss='categorical_crossentropy',
              metrics=['accuracy'])

neural_model = neural_model.fit(
    X_train_scaled,
    y_train_categorical,
    epochs=200,
    shuffle=True,
    verbose=2
)

from sklearn.externals import joblib 

joblib.dump(neural_model, 'neural.pkl') 
# also tried dump(neural_model, 'neural.joblib')```

Error message: can't pickle _thread.RLock objects

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不建议使用pickle或cPickle保存Keras模型

您只需执行以下操作：

model.save（文件路径）

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