Changes in v1.4.1
- Add
grouptosmooth_lss()to smooth scores by group. - Add
optimize_lss()as an experimental function.
Changes in v1.4.0
CRAN release: 2024-03-05
- Change the default value to
max_highlighted = 1000intextplot_terms(). - Add
...to customize text labels totextplot_terms(). - Highlight words in different colors when a dictionary is passed to
highlighted. - Add
mode = "predict"andremove = FALSEtobootstrap_lss().
Changes in v1.3.2
CRAN release: 2023-12-20
- Fix the error in
textplot_terms()when the frequency of terms are zero (#85).
Changes in v1.3.1
CRAN release: 2023-02-26
- Fix the range of scores when
cutis used. - Add
bootstrap_lss()as an experimental function.
Changes in v1.3.0
CRAN release: 2023-01-22
- Add
cuttopredict. - Move examples to the new package website: http://koheiw.github.io/LSX.
- Rename “rescaling” to “rescale” for simplicity and consistency.
- Improve random sampling of words to highlight in
textplot_terms()to avoid congestion.
Changes in v1.2.0
CRAN release: 2022-12-04
- Add
group_datatotextmodel_lss()to simplify the workflow. - Add
max_highlightedtotextplot_terms()to automatically highlight polarity words.
Changes in v1.1.4
- Update
as.textmodel_lss()to avoid errors intextplot_terms()whentermsis used.
Changes in v1.1.3
CRAN release: 2022-10-19
- Restore examples for
textmodel_lss(). - Defunct
char_keyness()that has been deprecated for long.
Changes in v1.1.1
CRAN release: 2022-02-26
- Add
min_ntopredict()to make polarity scores of short documents more stable.
Changes in v1.1.0
CRAN release: 2022-02-24
- Add
as.textmodel_lss()for textmodel_lss objects to allow modifying existing models. - Allow
termsintextmodel_lss()to be a named numeric vector to give arbitrary weights.
Changes in v1.0.2
CRAN release: 2021-09-18
- Add the
auto_weightargument totextmodel_lss()andas.textmodel_lss()to improve the accuracy of scaling. - Remove the
groupargument fromtextplot_simil()to simplify the object. - Make
as.seedwords()to accept multiple indices forupperandlower.
Changes in v1.0.0
CRAN release: 2021-07-20
- Add
max_counttotextmodel_lss.fcm()that will be passed tox_maxinrsparse::GloVe$new(). - Add
max_wordstotextplot_terms()to avoid overcrowding. - Make
textplot_terms()to work with objects fromtextmodel_lss.fcm(). - Add
concatenatortoas.seedwords().
Changes in v0.9.9
CRAN release: 2021-04-19
- Correct how
textstat_context()andchar_context()computes statistics. - Deprecate
char_keyness().
Changes in v0.9.8
CRAN release: 2021-03-22
- Stop using functions and arguments deprecated in quanteda v3.0.0.
Changes in v0.9.7
CRAN release: 2021-03-08
- Make
as.textmodel_lss.matrix()more reliable. - Remove quanteda.textplots from dependencies.
Changes in v0.9.6
CRAN release: 2020-12-17
- Updated to reflect changes in quanteda (creation of quanteda.textstats).
Changes in v0.9.4
CRAN release: 2020-11-02
- Fix
char_context()to always return more frequent words in context. - Experimental
textplot_factor()has been removed. -
as.textmodel_lss()takes a pre-trained word-embedding.
Changes in v0.9.3
- Add
textstat_context()andchar_context()to replacechar_keyness(). - Make the absolute sum of seed weight equal to 1.0 in both upper and lower ends.
-
textplot_terms()takes glob patterns in character vector or a dictionary object. -
char_keyness()no longer raise error when no patter is found in tokens object. - Add
enginetosmooth_lss()to applylocfit()to large datasets.
Changes in v0.9.2
CRAN release: 2020-09-22
- Updated unit tests for the new versions of stringi and quanteda.
Changes in v0.8.7
- Added
textplot_terms()to improve visualization of model terms.