代码示例(调整模型的超参数):
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
# 构建模型
model = Sequential([
Dense(units=32, activation='relu', input_shape=(7,)),
Dense(units=16, activation='relu'),
Dense(units=8, activation='relu'),
Dense(units=1, activation='sigmoid')
])
# 编译模型
model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])
# 超参数
epochs = 100
batch_size = 64
learning_rate = 0.001
# 训练模型
history = model.fit(X_train, y_train,
epochs=epochs,
batch_size=batch_size,
validation_data=(X_val, y_val))
# 输出模型准确率
_, accuracy = model.evaluate(X_test, y_test)
print('Test accuracy:', accuracy)
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