我正在尝试自学如何在基本的多层神经网络中使用网格搜索来确定神经元数量。我使用Python的GridSearchCV和KerasClasifier以及Keras。下面的代码在其他数据集上运行良好，但我无法使其在鸢尾花数据集上正常工作，并且我找不到原因，我在这里缺少了什么。我得到的结果是：
最佳结果: 0.000000，使用{'n_neurons': 3}
与 {'n_neurons': 3} 一起使用：0.000000（0.000000）
与 {'n_neurons': 5} 一起使用：0.000000（0.000000）
from pandas import read_csv
import numpy
from sklearn.preprocessing import LabelEncoder
from sklearn.preprocessing import StandardScaler
from keras.wrappers.scikit_learn import KerasClassifier
from keras.models import Sequential
from keras.layers import Dense
from keras.utils import np_utils
from sklearn.model_selection import GridSearchCV
dataframe=read_csv("iris.csv", header=None)
dataset=dataframe.values
X=dataset[:,0:4].astype(float)
Y=dataset[:,4]
seed=7
numpy.random.seed(seed)
#encode class values as integers
encoder = LabelEncoder()
encoder.fit(Y)
encoded_Y = encoder.transform(Y)
#one-hot encoding
dummy_y = np_utils.to_categorical(encoded_Y)
#scale the data
scaler = StandardScaler()
X = scaler.fit_transform(X)
def create_model(n_neurons=1):
#create model
model = Sequential()
model.add(Dense(n_neurons, input_dim=X.shape[1], activation='relu')) # hidden layer
model.add(Dense(3, activation='softmax')) # output layer
# Compile model
model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
return model
model = KerasClassifier(build_fn=create_model, epochs=100, batch_size=10, initial_epoch=0, verbose=0)
# define the grid search parameters
neurons=[3, 5]
#this does 3-fold classification. One can change k.
param_grid = dict(n_neurons=neurons)
grid = GridSearchCV(estimator=model, param_grid=param_grid, n_jobs=-1)
grid_result = grid.fit(X, dummy_y)
# summarize results
print("Best: %f using %s" % (grid_result.best_score_, grid_result.best_params_))
means = grid_result.cv_results_['mean_test_score']
stds = grid_result.cv_results_['std_test_score']
params = grid_result.cv_results_['params']
for mean, stdev, param in zip(means, stds, params):
print("%f (%f) with: %r" % (mean, stdev, param))
为了举例说明和提高计算效率，我只搜索两个值。非常抱歉我提出了这样一个简单的问题。我是Python的新手，顺便说一下，我从R转到Python，因为我意识到深度学习社区正在使用Python。