Changes in v1.2.1
- Fix tests on systems when the TBB library is unavailable.
Changes in v1.2.0
- The RcppParallel package is no longer required as the TBB library in the operating system (Linux and MacOS) or Rtools (Windows) is used.
- Linux and MacOS must have the TBB library to enable parallel computing before installing this package from the source.
Changes in v1.1.1
- Allow
alpha
and beta
to be a vector for asymmetric Dirichlet priors.
Changes in v1.1.0
- Remove
uniform
to simplify the computation of seed word weights.
- Add
levels
argument to better handle hierarchical dictionaries.
Changes in v1.0.1
- Fix the error when
textmodel_seqlda()
is called.
- Save values in the Array object in double to avoid rounding error (#60).
Changes in v1.0.0
- Add
auto_iter
to textmodel_seededlda()
and textmodel_lda()
to stop Gibbs sampling automatically before max_iter
is reached.
- Add
batch_size
to textmodel_seededlda()
and textmodel_lda()
to enable the distributed LDA algorithm for parallel computing.
Changes in v0.9.0
- Add the gamma parameter to
textmodel_seededlda()
and textmodel_lda()
for sequential classification.
- Add
textmodel_seqlda()
as as short cut for textmodel_lda(gamma = 0.5)
.
- Improve the calculation of weights for seed words.
- Add the
regularize
argument to divergence()
for the regularized topic divergence measure.
Changes in v0.8.4
- Fix for deprecation in Matrix 1.5-4.
Changes in v0.8.3
- Add
data_corpus_moviereviews
to the package to reduce dependency.
Changes in v0.8.2
- Add
min_prob
and select
to topics()
for greater flexibility
- Change the divergence measure from Kullback-Leibler to Jensen-Shannon.
- Add
weighted
, min_size
, select
to divergence()
for regularized topic divergence scores.
Changes in v0.8.1
- Change
textmodel_seededlda()
to set positive integer values to residual
.
- Fix a bug in
textmodel_seededlda()
that ignores n-grams when concatenator
is not "_".
- Change
topics()
to return document names.
- Add
divergence()
to optimize the number of topics or the seed words (#26).
Changes in v0.8.0
- Add the
model
argument to textmodel_lda()
to replace predict()
.
Changes in v0.7.0
- Change the
textmodel_seededlda
object to save dictionary and related settings (#18)
Changes in v0.6.0
- Add
predict()
to identify topics of unseen documents (#9)
- Allow selecting seed words based on their frequencies using
dfm_trim()
in textmodel_seededlda()
via ...
(#8)
Changes in v0.5.1
- Change
topics()
to return factor with NA for empty documents
- Fix a bug in initializing LDA that leads to incorrect phi (#4 and #6)
Changes in v0.5
- Implement original LDA estimator using the LDAGibbs++ library