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| context_type |
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| sents |
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| dtype |
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| matrix |
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def vsm.model.beaglecontext.BeagleContextMulti.__init__ |
( |
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self, |
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corpus, |
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env_corpus, |
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env_matrix, |
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context_type = 'sentence' |
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) |
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Initialize BeagleContextMulti.
:param corpus: Souce of observed data.
:type corpus: class:`Corpus`
:param env_corpus: BEAGLE environment corpus.
:type env_corpus: class:`Corpus`
:param env_matrix: Matrix from BEAGLE environment model.
:type env_matrix: 2-D array
:param context_type: Name of tokenization stored in `corpus` whose
tokens will be treated as documents. Default is `sentence`.
:type context_type: string, optional
def vsm.model.beaglecontext.BeagleContextMulti.train |
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self, |
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n_procs = 2 |
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) |
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Takes an optional argument `n_procs`, number of processors,
and trains the model on the number of processors. `n_procs`
is 2 by default.
:param n_procs: Number of processors. Default is 2.
:type n_procs: int, optional
:returs: `None`
La documentación para esta clase fue generada a partir del siguiente fichero:
- vsm/vsm/model/beaglecontext.py