asterism.core.lda#
Module contents#
- class asterism.core.lda.GibbsLDA(n_topics=5, *, doc_size=32, vocab_size=16, dt_prior=1.0, tw_prior=1.0, desc='LDA', seed=None)#
Bases:
Asterism- set_fit_request(*, display_rate: bool | None | str = '$UNCHANGED$', locs: bool | None | str = '$UNCHANGED$', n_steps: bool | None | str = '$UNCHANGED$', verbosity: bool | None | str = '$UNCHANGED$', x: bool | None | str = '$UNCHANGED$') GibbsLDA#
Configure whether metadata should be requested to be passed to the
fitmethod.Note that this method is only relevant when this estimator is used as a sub-estimator within a meta-estimator and metadata routing is enabled with
enable_metadata_routing=True(seesklearn.set_config()). Please check the User Guide on how the routing mechanism works.The options for each parameter are:
True: metadata is requested, and passed tofitif provided. The request is ignored if metadata is not provided.False: metadata is not requested and the meta-estimator will not pass it tofit.None: metadata is not requested, and the meta-estimator will raise an error if the user provides it.str: metadata should be passed to the meta-estimator with this given alias instead of the original name.
The default (
sklearn.utils.metadata_routing.UNCHANGED) retains the existing request. This allows you to change the request for some parameters and not others.Added in version 1.3.
Parameters#
- display_ratestr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED
Metadata routing for
display_rateparameter infit.- locsstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED
Metadata routing for
locsparameter infit.- n_stepsstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED
Metadata routing for
n_stepsparameter infit.- verbositystr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED
Metadata routing for
verbosityparameter infit.- xstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED
Metadata routing for
xparameter infit.
Returns#
- selfobject
The updated object.
- class asterism.core.lda.GibbsSLDA(n_topics=5, *, n_docs=-16, doc_size=6.0, word_size=6.0, vocab_size=16, dt_prior=1.0, tw_prior=1.0, desc='SLDA', seed=None)#
Bases:
Asterism- fit(x, locs, y=None, *args, **kwargs)#
- fit_predict(x, locs, y=None, *args, **kwargs)#
Perform clustering on X and returns cluster labels.
Parameters#
- Xarray-like of shape (n_samples, n_features)
Input data.
- yIgnored
Not used, present for API consistency by convention.
- **kwargsdict
Arguments to be passed to
fit.Added in version 1.4.
Returns#
- labelsndarray of shape (n_samples,), dtype=np.int64
Cluster labels.
- set_fit_request(*, locs: bool | None | str = '$UNCHANGED$', x: bool | None | str = '$UNCHANGED$') GibbsSLDA#
Configure whether metadata should be requested to be passed to the
fitmethod.Note that this method is only relevant when this estimator is used as a sub-estimator within a meta-estimator and metadata routing is enabled with
enable_metadata_routing=True(seesklearn.set_config()). Please check the User Guide on how the routing mechanism works.The options for each parameter are:
True: metadata is requested, and passed tofitif provided. The request is ignored if metadata is not provided.False: metadata is not requested and the meta-estimator will not pass it tofit.None: metadata is not requested, and the meta-estimator will raise an error if the user provides it.str: metadata should be passed to the meta-estimator with this given alias instead of the original name.
The default (
sklearn.utils.metadata_routing.UNCHANGED) retains the existing request. This allows you to change the request for some parameters and not others.Added in version 1.3.
Parameters#
- locsstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED
Metadata routing for
locsparameter infit.- xstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED
Metadata routing for
xparameter infit.
Returns#
- selfobject
The updated object.
- class asterism.core.lda.PyroLDA(n_topics=5, *, doc_size=32, vocab_size=16, dt_prior=1.0, tw_prior=1.0, desc='LDA', seed=None)#
Bases:
Asterism,Module- set_fit_request(*, display_rate: bool | None | str = '$UNCHANGED$', locs: bool | None | str = '$UNCHANGED$', n_steps: bool | None | str = '$UNCHANGED$', verbosity: bool | None | str = '$UNCHANGED$', x: bool | None | str = '$UNCHANGED$') PyroLDA#
Configure whether metadata should be requested to be passed to the
fitmethod.Note that this method is only relevant when this estimator is used as a sub-estimator within a meta-estimator and metadata routing is enabled with
enable_metadata_routing=True(seesklearn.set_config()). Please check the User Guide on how the routing mechanism works.The options for each parameter are:
True: metadata is requested, and passed tofitif provided. The request is ignored if metadata is not provided.False: metadata is not requested and the meta-estimator will not pass it tofit.None: metadata is not requested, and the meta-estimator will raise an error if the user provides it.str: metadata should be passed to the meta-estimator with this given alias instead of the original name.
The default (
sklearn.utils.metadata_routing.UNCHANGED) retains the existing request. This allows you to change the request for some parameters and not others.Added in version 1.3.
Parameters#
- display_ratestr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED
Metadata routing for
display_rateparameter infit.- locsstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED
Metadata routing for
locsparameter infit.- n_stepsstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED
Metadata routing for
n_stepsparameter infit.- verbositystr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED
Metadata routing for
verbosityparameter infit.- xstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED
Metadata routing for
xparameter infit.
Returns#
- selfobject
The updated object.