Logisticregression is default for classification in textTrain.
textSimilarityTest()when uneven number of cases are tested.
textDistance()function with distance measures.
textTrainRegression()concatenates word embeddings when provided with a list of several word embeddings.
textCentrality(), words to be plotted are selected with
word_data1_all$extremes_all_x >= 1(rather than
textSimilarityMatrix()computes semantic similarity among all combinations in a given word embedding.
textDescriptives()gets options to remove NA and compute total scores.
textProjetionPlot()it now possible to add points of the aggregated word embeddings in the plot
textProjetion()it now possible to manually add words to the plot in order to explore them in the word embedding space.
textProjetion()it is possible to add color or remove words that are more frequent on the opposite “side” of its dot product projection.
split == quartile, the comparison distribution is now based on the quartile data (rather than the data for mean)
textSimilarityTest()is not giving error when using method = unpaired, with unequal number of participants in each group.
textPredictTest()function to significance test correlations of different models. 0.9.11
This version is now on CRAN. ### New Features - Adding option to deselect the
step_scale in training. - Cross-validation method in
textTrainRandomForrest() have two options
validation_split. (0.9.02) - Better handling of
step_naomit in training. -
DistilBert model works (0.9.03)
textProjectionPlot()plots words extreme in more than just one feature (i.e., words are now plotted that satisfy, for example, both
textTrainRandomForest()also have function that select the max evaluation measure results (before only minimum was selected all the time, which, e.g., was correct for rmse but not for r) (0.9.02)
id_nrin training and predict by using workflows (0.9.02).