How to compile a model in Keras.

10 months ago

Liam

1 minute

In order to compile a model in Keras, you can utilize the `compile()` method of the model object. Within the `compile()` method, you can specify the optimizer, loss function, and metrics.

Here is an example code for a compiler model:

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

# 创建一个简单的全连接神经网络模型
model = Sequential()
model.add(Dense(units=64, activation='relu', input_dim=100))
model.add(Dense(units=10, activation='softmax'))

# 编译模型
model.compile(optimizer='adam',
              loss='categorical_crossentropy',
              metrics=['accuracy'])

In the code above, we first create a simple fully connected neural network model, then compile the model using the compile() method. In the compile() method, we specify the optimizer as Adam, the loss function as categorical crossentropy, and the evaluation metric as accuracy.

Once the model is compiled, you can use the fit() method to train the model.