#-*- coding: UTF-8 -*-
from sklearn.model_selection import train_test_split
def split(dataset, labelset, test_size, train_savefile, test_savefile):
# split into training set and test set
x_train, x_test, y_train, y_test = train_test_split(dataset, labelset, test_size=test_size, random_state=42, stratify=labelset )
savetxt(train_savefile, x_train)
savetxt(test_savefile, x_test)
return x_train, x_test
def savetxt(path, np_array):
with open(file=path, mode='w', encoding='utf-8') as fw:
fw.writelines(np_array)
def reader_data(datafile):
data_list = []
with open(datafile, mode='r', encoding='utf-8') as f:
for line in f:
data_list.append(line)
return data_list
if __name__ == '__main__':
datafile = 'data/output/tra-set0603_0.9'
dataset = reader_data(datafile)
label_file = 'data/output/tra-set0603_0.9_label'
labelset = reader_data(label_file)
test_size = 0.2
train_savefile = 'data/output/raw_0.9/raw_train.txt'
test_savefile = 'data/output/raw_0.9/raw_test.txt'
split(dataset, labelset, test_size, train_savefile, test_savefile)
sklearn 划分数据集
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转载自blog.csdn.net/Cincinnati_De/article/details/80622948
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