R/2_1_textTrain.R
textTrainLists.Rd
Individually trains word embeddings from several text variables to several numeric or categorical variables. It is possible to have word embeddings from one text variable and several numeric/categprical variables; or vice verse, word embeddings from several text variables to one numeric/categorical variable. It is not possible to mix numeric and categorical variables.
textTrainLists(
x,
y,
force_train_method = "automatic",
save_output = "all",
method_cor = "pearson",
eval_measure = "rmse",
p_adjust_method = "holm",
...
)
Word embeddings from textEmbed (or textEmbedLayerAggreation).
Tibble with several numeric or categorical variables to predict. Please note that you cannot mix numeric and categorical variables.
Default is "automatic"; see also "regression" and "random_forest".
Option not to save all output; default "all". see also "only_results" and "only_results_predictions".
A character string describing type of correlation (default "Pearson").
Type of evaluative measure to assess models on.
Method to adjust/correct p-values for multiple comparisons (default = "holm"; see also "none", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr").
Arguments from textTrainRegression or textTrainRandomForest the textTrain function.
Correlations between predicted and observed values.
if (FALSE) {
word_embeddings <- word_embeddings_4$texts[1:2]
ratings_data <- Language_based_assessment_data_8[5:6]
results <- textTrainLists(
x = word_embeddings,
y = ratings_data
)
results
comment(results)
}