python indices,python – 什么“indices参数被弃用并将被删除(假设为True)0.17”是什么意思？...

我刚开始学习python并道歉,如果这是一个非常基本的问题/错误.

我在做Kaggle生物反应教程.我收到了这个错误

C:\Anaconda\lib\site-packages\sklearn\cross_validation.py:65:

DeprecationWarning: The indices parameter is deprecated and will be

removed (assumed True) in 0.17 stacklevel=1) Results: 0.458614231133

谁知道这意味着什么？我谷歌它死了,找不到答案.

我正在运行的脚本是：

from sklearn.ensemble import RandomForestClassifier

from sklearn import cross_validation

import logloss

import numpy as np

def main():

#read in data, parse into training and target sets

dataset = np.genfromtxt(open('train.csv','r'), delimiter=',', dtype='f8')[1:]

target = np.array([x[0] for x in dataset])

train = np.array([x[1:] for x in dataset])

#In this case we'll use a random forest, but this could be any classifier

cfr = RandomForestClassifier(n_estimators=100)

#Simple K-Fold cross validation. 5 folds.

#(Note: in older scikit-learn versions the "n_folds" argument is named "k".)

cv = cross_validation.KFold(len(train), n_folds=5, indices=False)

#iterate through the training and test cross validation segments and

#run the classifier on each one, aggregating the results into a list

results = []

for traincv, testcv in cv:

probas = cfr.fit(train[traincv], target[traincv]).predict_proba(train[testcv])

results.append( logloss.llfun(target[testcv], [x[1] for x in probas]) )

#print out the mean of the cross-validated results

print "Results: " + str( np.array(results).mean() )

if __name__=="__main__":

main()

我相信这是在说：

__author__ = 'nickd'

import scipy as sp

def llfun(act, pred):

epsilon = 1e-15

pred = sp.maximum(epsilon, pred)

pred = sp.minimum(1-epsilon, pred)

ll = sum(act*sp.log(pred) + sp.subtract(1,act)*sp.log(sp.subtract(1,pred)))

ll = ll * -1.0/len(act)

return ll

再一次,真的很抱歉,如果这是基本的东西.我以前真的从未这样做过.

解决方法:

这意味着您使用indices关键字参数调用cross_validation.KFold时未来版本将不支持它：

cv = cross_validation.KFold(len(train), n_folds=5, indices=False)

根据错误消息,您将获得index = True的效果,为0.17.该消息表明他们将删除关键字参数,可能他们不会忽略未使用的关键字参数,因此,如果您继续尝试传入索引,可能会在0.17中获得TypeError异常.

标签：python,python-2-7,machine-learning,kaggle

来源： https://codeday.me/bug/20190528/1169668.html