NEWS.md

In quanteda.textmodels: Scaling Models and Classifiers for Textual Data

quanteda.textmodels 0.9.5

• Fixes for compatibility with Matrix 1.4.2.

quanteda.textmodels 0.9.4

• removed data_dfm_lbgexample as this is already in quanteda.

quanteda.textmodels 0.9.3

• Fixed textmodel_svm() to default to the "L2-regularized L2-loss support vector classification (dual)" model, and added the type argument to allow this to be overridden. (#45)
• Loosened a test tolerance that was causing a text to fail on the macM1 platform.

quanteda.textmodels 0.9.2

• Added a logistic regression classifier, textmodel_lr().
• Simplified textmodel_svmlin() to implement only the L2-SVM-MFN from Sindhwani and Keerthi (2006), and now uses the C++ code natively.

quanteda.textmodels 0.9.1

• Adds data_corpus_dailnoconf1991 and data_corpus_irishbudget2010 corpus objects moved from the quanteda package.
• Adds the Pang and Lee (2004) movie review polarity dataset as data_corpus_moviereviews.
• Fixed a bug in textmodel_nb(x, distribution = "Bernoulli") that affected the class conditional probabilities when the number of classes was > 2.
• Doubled the performance of textmodel_nb() - it's now officially the fastest implementation in R. (See the vignette.)

quanteda.textmodels 0.9.0

• First implementation of the package, after splitting these functions from the quanteda package.

quanteda.textmodels documentation built on March 31, 2023, 8:09 p.m.