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

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.

See also

textTrainRegression textTrainRandomForest textTrainLists textSimilarityTest

Examples

if (FALSE) {
wordembeddings <- wordembeddings4
ratings_data <- Language_based_assessment_data_8
results <- textTrain(
  wordembeddings$harmonytext,
  ratings_data$hilstotal
)
}