使用遗传算法对 ANN keras 模型进行超参数优化

Question

我想使用 sklearn_genic 库中的 GASearchCV 来优化我的 keras 模型的超参数。首先，我定义了一个函数来构建我的模型。然后我使用 scikeras 来创建我的估算器。最后我调用GASearchCV来优化超参数，然后将其拟合到数据上。代码在这里：

import tensorflow as tf
from tensorflow import keras
from scikeras.wrappers import KerasClassifier
from sklearn_genetic import GASearchCV

def ann_model_ga(number_of_hidden_layer=1,
                 number_of_neurons=50,
                 optimizer="adam"):
    model = keras.models.Sequential()
    model.add(keras.layers.Flatten(input_shape=X_train.shape[1:]))
    for hidden_layer in range(number_of_hidden_layer):
        model.add(keras.layers.Dense(number_of_neurons))
    model.add(keras.layers.Dense(10, activation="softmax"))
    model.compile(optimizer=optimizer, loss="categorical_crossentropy", metrics=["accuracy", "AUC"],)
    return model
param_grid = {'number_of_hidden_layer': Integer(1, 5),
              'number_of_neurons': Integer(100, 200),
              'optimizer': Categorical(["adam", "sgd"])}

estimator = KerasClassifier(build_fn=ann_model_ga)

evolved_estimator = GASearchCV(estimator=estimator,
                               cv=5,
                               scoring='accuracy',
                               population_size=10,
                               generations=35,
                               tournament_size=3,
                               elitism=True,
                               crossover_probability=0.8,
                               mutation_probability=0.1,
                               param_grid=param_grid,
                               criteria='max',
                               algorithm='eaMuPlusLambda',
                               n_jobs=-1,
                               verbose=True,
                               keep_top_k=4)
history_ga = evolved_estimator.fit(X_train, y_train)

但是我收到了这个错误：

ValueError                                Traceback (most recent call last)
<ipython-input-17-36285fd9a509> in <cell line: 1>()
----> 1 history_ga = evolved_estimator.fit(X_train, y_train)

4 frames
/usr/local/lib/python3.10/dist-packages/scikeras/wrappers.py in set_params(self, **params)
   1163                     # Give a SciKeras specific user message to aid
   1164                     # in moving from the Keras wrappers
-> 1165                     raise ValueError(
   1166                         f"Invalid parameter {param} for estimator {self.__name__}."
   1167                         "\nThis issue can likely be resolved by setting this parameter"

ValueError: Invalid parameter number_of_hidden_layer for estimator KerasClassifier.
This issue can likely be resolved by setting this parameter in the KerasClassifier constructor:
`KerasClassifier(number_of_hidden_layer=1)`
Check the list of available parameters with `estimator.get_params().keys()`

有人可以帮我解决这个问题吗？