Train word embeddings to a numeric (ridge regression) or categorical (random forest) variable.

Source: R/2_1_textTrain.R

Train word embeddings to a numeric (ridge regression) or categorical (random forest) variable.

textTrain(x, y, force_train_method = "automatic", ...)

Arguments

x

Word embeddings from textEmbed (or textEmbedLayerAggreation). Can analyze several variables at the same time; but if training to several outcomes at the same time use a tibble within the list as input rather than just a tibble input (i.e., keep the name of the wordembedding).

y

Numeric variable to predict. Can be several; although then make sure to have them within a tibble (this is required even if it is only one outcome but several word embeddings variables).

force_train_method

default is "automatic", so if y is a factor random_forest is used, and if y is numeric ridge regression is used. This can be overridden using "regression" or "random_forest".

...

Arguments from textTrainRegression or textTrainRandomForest the textTrain function.

Value

A correlation between predicted and observed values; as well as a tibble of predicted values.

Examples

if (FALSE) {
word_embeddings <- word_embeddings_4
ratings_data <- Language_based_assessment_data_8
results <- textTrain(
  x = word_embeddings$harmonytext,
  y = ratings_data$hilstotal
)
}