解决 Hands-On-Machine-Learning实战第三章数据无法加载问题

下面是具体加载代码，亲测可用。但是需要点时间。

from six.moves import urllib
from sklearn.datasets import fetch_mldata
#try:
 #   mnist = fetch_mldata('MNIST original')
#except urllib.error.HTTPError as ex:
#print("Could not download MNIST data from mldata.org, trying alternative...")

# Alternative method to load MNIST, if mldata.org is down
from scipy.io import loadmat
mnist_alternative_url = "https://github.com/amplab/datascience-sp14/raw/master/lab7/mldata/mnist-original.mat"
mnist_path = "./mnist-original.mat"
response = urllib.request.urlopen(mnist_alternative_url)
with open(mnist_path, "wb") as f:
    content = response.read()
    f.write(content)
mnist_raw = loadmat(mnist_path)
mnist = {
    "data": mnist_raw["data"].T,
    "target": mnist_raw["label"][0],
    "COL_NAMES": ["label", "data"],
    "DESCR": "mldata.org dataset: mnist-original",
}
print("Success!")

Success!

mnist

 

Out[9]:
{'COL_NAMES': ['label', 'data'],
 'DESCR': 'mldata.org dataset: mnist-original',
 'data': array([[0, 0, 0, ..., 0, 0, 0],
        [0, 0, 0, ..., 0, 0, 0],
        [0, 0, 0, ..., 0, 0, 0],
        ...,
        [0, 0, 0, ..., 0, 0, 0],
        [0, 0, 0, ..., 0, 0, 0],
        [0, 0, 0, ..., 0, 0, 0]], dtype=uint8),
 'target': array([0., 0., 0., ..., 9., 9., 9.])}