python创建数据集_如何在scikitlearn中创建自己的数据集？

这里有一个快速而肮脏的方法来达到你的目的：

我的_数据集.py在import numpy as np

import csv

from sklearn.datasets.base import Bunch

def load_my_fancy_dataset():

with open('my_fancy_dataset.csv') as csv_file:

data_file = csv.reader(csv_file)

temp = next(data_file)

n_samples = int(temp[0])

n_features = int(temp[1])

data = np.empty((n_samples, n_features))

target = np.empty((n_samples,), dtype=np.int)

for i, sample in enumerate(data_file):

data[i] = np.asarray(sample[:-1], dtype=np.float64)

target[i] = np.asarray(sample[-1], dtype=np.int)

return Bunch(data=data, target=target)

我的幻想_数据集.csv在

^{pr2}$

演示In [12]: import my_datasets

In [13]: mfd = my_datasets.load_my_fancy_dataset()

In [14]: X = mfd.data

In [15]: y = mfd.target

In [16]: X

Out[16]:

array([[ 5.90000000e+00, 1.20300000e+03, 6.90000000e-01],

[ 7.20000000e+00, 9.02000000e+02, 5.20000000e-01],

[ 6.30000000e+00, 1.43000000e+02, 4.40000000e-01],

[ -2.60000000e+00, 2.91000000e+02, 1.50000000e-01],

[ 1.80000000e+00, 4.86000000e+02, 3.70000000e-01]])

In [17]: y

Out[17]: array([2, 0, 1, 1, 0])