问python：估计器KerasClassifier参数hidden_layers无效？

提问于 2024-08-02 01:37:53

回答 0关注 0查看 18

在利用网格搜索进行寻优操作时，出现了以下错误：

ValueError: Invalid parameter hidden_layers for estimator KerasClassifier.

This issue can likely be resolved by setting this parameter in the KerasClassifier constructor:

`KerasClassifier(hidden_layers=1)`

Check the list of available parameters with `estimator.get_params().keys()`

以下是源代码：

from sklearn import svm, datasets
from sklearn.model_selection import GridSearchCV
from keras.src.models.sequential import Sequential
from scikeras.wrappers import KerasClassifier
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import Dense
from sklearn.model_selection import GridSearchCV
import pandas as pd
from scikeras.wrappers import KerasRegressor

# 定义模型构建函数
def create_model(hidden_layers=1, units=50):
    model = Sequential()
    model.add(Dense(units=units, activation='relu', input_dim=6))
    for _ in range(hidden_layers - 1):
        model.add(Dense(units=units, activation='relu'))
    model.add(Dense(1, activation='sigmoid'))
    model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
    return model

# 包装成KerasClassifier
model = KerasClassifier(build_fn=create_model, epochs=50, batch_size=256, verbose=0)


# 定义参数网格
param_grid = {
    'hidden_layers': [1, 2, 3],
    'units': [1,2,3,4,5,6,7,8,8,9,10,11,12,13,14,15,16,17,18,19,20]
}

# 初始化GridSearchCV
grid = GridSearchCV(estimator=model, param_grid=param_grid, scoring='accuracy', cv=3)

# 导入数据
dataset_train = pd.read_excel("F:\桌面\BPNN_NOx排放预测\Bayes-Newdata_25.xlsx")
dataset_test = pd.read_excel("F:\桌面\BPNN_NOx排放预测\Small_data_25.xlsx")
dataset_train.tail()

# 数据预处理(归一化与数据集的划分)
scaler = MinMaxScaler()
train_scaler = scaler.fit_transform(dataset_train) # 默认是[0,1]
test_scaler = scaler.transform(dataset_test)

# 划分输入输出
X_train = train_scaler[:, :-1]
Y_train = train_scaler[:,-1]
X_test = test_scaler[:, :-1]
Y_test = test_scaler[:,-1]

# 执行搜索
grid_result = grid.fit(X_train, Y_train)

# 输出最佳参数和得分
print("Best: %f using %s" % (grid_result.best_score_, grid_result.best_params_))

求解答，谢谢大佬！！！！！

python