textTrain() trains 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 (t-value, degree of freedom (df), p-value,
alternative-hypothesis, confidence interval, correlation coefficient).

## Examples

```
# Examines how well the embeddings from "harmonytext" can
# predict the numeric variable "hilstotal" in the pre-included
# dataset "Language_based_assessment_data_8".
if (FALSE) { # \dontrun{
trained_model <- textTrain(
x = word_embeddings_4$texts$harmonytext,
y = Language_based_assessment_data_8$hilstotal
)
# Examine results (t-value, degree of freedom (df), p-value,
# alternative-hypothesis, confidence interval, correlation coefficient).
trained_model$results
} # }
```