Can't load 'mnist-original' dataset using sklearn

Question

This question is similar to what asked here and here. Unfortunately, in my case the suggested solution didn't fix the problem.

I need to work with the MNIST dataset but I can't fetch it, even if I specify the address of the scikit_learn_data/mldata/ folder (see below). How can I fix this?

In case it might help, I'm using Anaconda.

Code:

from sklearn.datasets.mldata import fetch_mldata

dataset = fetch_mldata('mnist-original', data_home='/Users/michelangelo/scikit_learn_data/mldata/')
mnist = fetch_mldata('MNIST original')

Error:

---------------------------------------------------------------------------
IOError                                   Traceback (most recent call last)
<ipython-input-5-dc4d45bc928e> in <module>()
----> 1 mnist = fetch_mldata('MNIST original')

/Users/michelangelo/anaconda2/lib/python2.7/site-packages/sklearn/datasets/mldata.pyc in fetch_mldata(dataname, target_name, data_name, transpose_data, data_home)
    168     # load dataset matlab file
    169     with open(filename, 'rb') as matlab_file:
--> 170         matlab_dict = io.loadmat(matlab_file, struct_as_record=True)
    171 
    172     # -- extract data from matlab_dict

/Users/michelangelo/anaconda2/lib/python2.7/site-packages/scipy/io/matlab/mio.pyc in loadmat(file_name, mdict, appendmat, **kwargs)
    134     variable_names = kwargs.pop('variable_names', None)
    135     MR = mat_reader_factory(file_name, appendmat, **kwargs)
--> 136     matfile_dict = MR.get_variables(variable_names)
    137     if mdict is not None:
    138         mdict.update(matfile_dict)

/Users/michelangelo/anaconda2/lib/python2.7/site-packages/scipy/io/matlab/mio5.pyc in get_variables(self, variable_names)
    290                 continue
    291             try:
--> 292                 res = self.read_var_array(hdr, process)
    293             except MatReadError as err:
    294                 warnings.warn(

/Users/michelangelo/anaconda2/lib/python2.7/site-packages/scipy/io/matlab/mio5.pyc in read_var_array(self, header, process)
    250            `process`.
    251         '''
--> 252         return self._matrix_reader.array_from_header(header, process)
    253 
    254     def get_variables(self, variable_names=None):

mio5_utils.pyx in scipy.io.matlab.mio5_utils.VarReader5.array_from_header()

mio5_utils.pyx in scipy.io.matlab.mio5_utils.VarReader5.array_from_header()

mio5_utils.pyx in scipy.io.matlab.mio5_utils.VarReader5.read_real_complex()

mio5_utils.pyx in scipy.io.matlab.mio5_utils.VarReader5.read_numeric()

mio5_utils.pyx in scipy.io.matlab.mio5_utils.VarReader5.read_element()

streams.pyx in scipy.io.matlab.streams.FileStream.read_string()

IOError: could not read bytes

Answer 1

I just faced the same issue and it took me some time to find the problem. One reason is, data can be corrupted during the first download. Remove the cached data. Find the scikit data home dir as follows:

from sklearn.datasets.base import get_data_home 
print (get_data_home())

Clean the directory and redownload the dataset. This solution works for me. For reference: https://github.com/ageron/handson-ml/issues/143

This is also related with the following question: How to use datasets.fetch_mldata() in sklearn?

Answer 2

A quick update for the question here:

mldata.org seems to still be down. Then scikit-learn will remove fetch_mldata.

Solution for the moment: Since using the lines above will create a empty folder a the place of data_home, find the copy of the data here: https://github.com/amplab/datascience-sp14/blob/master/lab7/mldata/mnist-original.mat and download it. Then place it the ~/sklearn_data/mldata/ which is empty.

It worked for me.

Answer 3

Instead of :

from sklearn.datasets.mldata import fetch_mldata

use:

from sklearn.datasets import fetch_mldata

And then:

mnist = fetch_mldata('MNIST original')
X = mnist.data.astype('float64')
y = mnist.target

Please see this example:

• http://scikit-learn.org/stable/auto_examples/linear_model/plot_sparse_logistic_regression_mnist.html#sphx-glr-auto-examples-linear-model-plot-sparse-logistic-regression-mnist-py

Answer 4

For people having the same issue: it was a connection problem. If you get a similar error, check that you have the entire mnist-original.mat file, as suggested by @vivek-kumar. Current file size: 55.4 MB.

Answer 5

In the latest sklearn version (0.21) use this:

import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.datasets import load_digits

digits = load_digits()

X = digits.data
y = digits.target

Answer 6

Try this one, this will work.

from sklearn.datasets import fetch_mldata
mnist = fetch_mldata('MNIST original')