39 lines
1.0 KiB
Python
39 lines
1.0 KiB
Python
# Sebastian Raschka 2014-2020
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# mlxtend Machine Learning Library Extensions
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#
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# A function for loading the open-source MNIST.
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# Author: Sebastian Raschka <sebastianraschka.com>
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#
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# License: BSD 3 clause
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import numpy as np
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import os
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this_dir, this_filename = os.path.split(__file__)
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DATA_PATH = os.path.join(this_dir, "data", "mnist_5k.csv.gz")
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def mnist_data():
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"""5000 samples from the MNIST handwritten digits dataset.
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Data Source : http://yann.lecun.com/exdb/mnist/
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Returns
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--------
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X, y : [n_samples, n_features], [n_class_labels]
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X is the feature matrix with 5000 image samples as rows,
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each row consists of 28x28 pixels that were unrolled into
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784 pixel feature vectors.
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y contains the 10 unique class labels 0-9.
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Examples
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-----------
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For usage examples, please see
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http://rasbt.github.io/mlxtend/user_guide/data/mnist_data/
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"""
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tmp = np.genfromtxt(fname=DATA_PATH, delimiter=',')
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X, y = tmp[:, :-1], tmp[:, -1]
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y = y.astype(int)
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return X, y
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