• 引言
• 代码

#!/usr/bin/python

# encoding: utf-8

"""

@version: 1.0

@author: Fly Lu

@license: Apache Licence

@contact: luyfuyu@gmail.com

@site: https://www.flyuuu.cn

@software: PyCharm

@file: sklearn_keras.py

@time: 2017-04-09 9:23

@description: 描述sklearn使用keras

"""

from keras.wrappers.scikit_learn import KerasClassifier

from keras.models import Sequential

from keras.layers import Dense

from sklearn.cross_validation import StratifiedKFold, cross_val_score

import numpy as np

def create_model():

    model = Sequential()

    model.add(Dense(12, input_dim=8, kernel_initializer='uniform', activation='relu'))

    model.add(Dense(8, kernel_initializer='uniform', activation='relu'))

    model.add(Dense(1, kernel_initializer='uniform', activation='sigmoid'))

    model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])

    return model

# 为了让每次的结果都相同

seed = 7

np.random.seed(seed)

# 加载数据

dataset = np.loadtxt('./data/pima-indians-diabetes.csv', delimiter=',')

X = dataset[:, 0:8]

Y = dataset[:, 8]

model = KerasClassifier(build_fn=create_model, epochs=150, batch_size=10)

kfold = StratifiedKFold(Y, n_folds=10, shuffle=True, random_state=seed)

results = cross_val_score(model, X, Y, cv=kfold)

print(np.average(results))