73 lines
2.4 KiB
ReStructuredText
73 lines
2.4 KiB
ReStructuredText
.. _rcv1_dataset:
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RCV1 dataset
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------------
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Reuters Corpus Volume I (RCV1) is an archive of over 800,000 manually
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categorized newswire stories made available by Reuters, Ltd. for research
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purposes. The dataset is extensively described in [1]_.
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**Data Set Characteristics:**
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============== =====================
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Classes 103
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Samples total 804414
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Dimensionality 47236
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Features real, between 0 and 1
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============== =====================
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:func:`sklearn.datasets.fetch_rcv1` will load the following
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version: RCV1-v2, vectors, full sets, topics multilabels::
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>>> from sklearn.datasets import fetch_rcv1
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>>> rcv1 = fetch_rcv1()
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It returns a dictionary-like object, with the following attributes:
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``data``:
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The feature matrix is a scipy CSR sparse matrix, with 804414 samples and
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47236 features. Non-zero values contains cosine-normalized, log TF-IDF vectors.
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A nearly chronological split is proposed in [1]_: The first 23149 samples are
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the training set. The last 781265 samples are the testing set. This follows
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the official LYRL2004 chronological split. The array has 0.16% of non zero
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values::
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>>> rcv1.data.shape
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(804414, 47236)
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``target``:
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The target values are stored in a scipy CSR sparse matrix, with 804414 samples
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and 103 categories. Each sample has a value of 1 in its categories, and 0 in
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others. The array has 3.15% of non zero values::
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>>> rcv1.target.shape
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(804414, 103)
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``sample_id``:
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Each sample can be identified by its ID, ranging (with gaps) from 2286
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to 810596::
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>>> rcv1.sample_id[:3]
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array([2286, 2287, 2288], dtype=uint32)
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``target_names``:
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The target values are the topics of each sample. Each sample belongs to at
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least one topic, and to up to 17 topics. There are 103 topics, each
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represented by a string. Their corpus frequencies span five orders of
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magnitude, from 5 occurrences for 'GMIL', to 381327 for 'CCAT'::
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>>> rcv1.target_names[:3].tolist() # doctest: +SKIP
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['E11', 'ECAT', 'M11']
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The dataset will be downloaded from the `rcv1 homepage`_ if necessary.
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The compressed size is about 656 MB.
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.. _rcv1 homepage: http://jmlr.csail.mit.edu/papers/volume5/lewis04a/
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.. topic:: References
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.. [1] Lewis, D. D., Yang, Y., Rose, T. G., & Li, F. (2004).
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RCV1: A new benchmark collection for text categorization research.
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The Journal of Machine Learning Research, 5, 361-397.
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