Changelog
Source:NEWS.md
Changes in v1.4.1
- Add
group
tosmooth_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 = 1000
intextplot_terms()
. - Add
...
to customize text labels totextplot_terms()
. - Highlight words in different colors when a dictionary is passed to
highlighted
. - Add
mode = "predict"
andremove = FALSE
tobootstrap_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
cut
is used. - Add
bootstrap_lss()
as an experimental function.
Changes in v1.3.0
CRAN release: 2023-01-22
- Add
cut
topredict
. - 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_data
totextmodel_lss()
to simplify the workflow. - Add
max_highlighted
totextplot_terms()
to automatically highlight polarity words.
Changes in v1.1.4
- Update
as.textmodel_lss()
to avoid errors intextplot_terms()
whenterms
is 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_n
topredict()
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
terms
intextmodel_lss()
to be a named numeric vector to give arbitrary weights.
Changes in v1.0.2
CRAN release: 2021-09-18
- Add the
auto_weight
argument totextmodel_lss()
andas.textmodel_lss()
to improve the accuracy of scaling. - Remove the
group
argument fromtextplot_simil()
to simplify the object. - Make
as.seedwords()
to accept multiple indices forupper
andlower
.
Changes in v1.0.0
CRAN release: 2021-07-20
- Add
max_count
totextmodel_lss.fcm()
that will be passed tox_max
inrsparse::GloVe$new()
. - Add
max_words
totextplot_terms()
to avoid overcrowding. - Make
textplot_terms()
to work with objects fromtextmodel_lss.fcm()
. - Add
concatenator
toas.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
engine
tosmooth_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.