Question

我正在用Python进行ANN，并且正在使用GridSearchCV（sklearn）为我的ANN寻找最佳参数。问题在于每次“ best_parameters”属性都返回每个参数的第一个元素（因此，如果我更改元素的顺序，则返回值是不同的。）

这是我的代码：

# Importing the libraries
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

from keras.models import Sequential
from keras.layers import Dense
from keras.wrappers.scikit_learn import KerasClassifier
from sklearn.model_selection import GridSearchCV

# Importing the dataset
dataset = pd.read_csv('data.csv')
X = dataset.iloc[:, 17:27].values
y = dataset.iloc[:, 3].values

# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.25, random_state = 0)

# Feature Scaling
from sklearn.preprocessing import StandardScaler
sc = StandardScaler()
X_train = sc.fit_transform(X_train)
X_test = sc.transform(X_test)

# Find best parameters
def build_classifier(optimizer):
    # Init ANN
    classifier = Sequential()
    # Add input and first hidden layers
    classifier.add(Dense(units=6, activation="relu", kernel_initializer="uniform", input_dim=10))
    # Add another hidder layer
    classifier.add(Dense(units=6, activation="relu", kernel_initializer="uniform"))
    # Add output layer
    classifier.add(Dense(units=1, activation="sigmoid", kernel_initializer="uniform"))
    # Compile ANN
    classifier.compile(optimizer=optimizer, loss="mean_squared_error")
    return classifier

# Looking for best parameters with GridSearchCV
classifier = KerasClassifier(build_fn=build_classifier)
parameters = {"batch_size":[1, 5, 10], "epochs":[100,200], "optimizer": ["rmsprop", "sgd", "adam"]}
grid_search = GridSearchCV(estimator=classifier, param_grid=parameters, scoring="neg_mean_squared_error", cv=10)
grid_search = grid_search.fit(X_train, y_train)

best_parameters = grid_search.best_params_
best_precision = grid_search.best_score_

因此，在parameters = {"batch_size":[1, 5, 10], "epochs":[100,200], "optimizer": ["rmsprop", "sgd", "adam"]}行中，我有要尝试的参数，属性“ best_parameters”始终返回每个参数的第一个元素（请检查图片，我尝试对参数进行几个排序）。 best_parameters return according to parameter order

我不知道这是从哪里来的以及如何纠正它。

Answer 1

我找到了解决方案，这是我做的一个错误... 我使用KerasClassifier来找到最佳参数，而我想进行回归...所以我想KerasClassifier未能成功完成他必须做的事情，然后返回第一个参数。由于我正在进行回归，因此我不得不使用KerasRegressor。

人工神经网络：GridSearchCV的错误每次都会返回第一个参数

1 个答案: