Releases: bab2min/tomotopy
Releases · bab2min/tomotopy
0.7.0
0.6.2
- A critical bug related to save and load was fixed. Version 0.6.0 and 0.6.1 have been removed from releases.
tomotopy.utils.Corpus
class that manages multiple documents easily was added.tomotopy.LDAModel.set_word_prior
method that controls word-topic priors of topic models was added.- A new argument
min_df
that filters words based on document frequency was added into every topic model's__init__
. tomotopy.label
, the submodule about topic labeling was added. Currently, onlytomotopy.label.FoRelevance
is provided.
0.5.2
0.5.1
- A bug was fixed that tomotopy.SLDAModel.make_doc doesn't support missing values for y.
- Now tomotopy.SLDAModel fully supports missing values for response variables y. Documents with missing values (NaN) are included in modeling topic, but excluded from regression of response variables.
0.5.0
- Now
tomotopy.PAModel.infer
returns both topic distribution nd sub-topic distribution. - New methods get_sub_topics and get_sub_topic_dist were added into
tomotopy.Document
. (for PAModel) - New parameter
parallel
was added fortomotopy.LDAModel.train
andtomotopy.LDAModel.infer
method. You can select parallelism algorithm by changing this parameter. tomotopy.ParallelScheme.PARTITION
, a new algorithm, was added. It works efficiently when the number of workers is large, the number of topics or the size of vocabulary is big.- A bug where
rm_top
didn't work atmin_cf
< 2 was fixed.
0.4.2
0.4.1
0.4.0
0.3.1
0.3.0
Update
- A new model,
tomotopy.LLDAModel
was added into the package. - Since hyperparameter estimation for
HDPModel
was implemented, the result ofHDPModel
may differ from previous versions. If you want to turn off hyperparameter estimation of HDPModel, setoptim_interval
to zero.
Fixed bugs
- A crashing issue of
HDPModel
was fixed. (#6)