bag_mlp | R Documentation |
bag_mlp()
defines an ensemble of single layer, feed-forward neural networks.
This function can fit classification and regression models.
More information on how parsnip is used for modeling is at https://www.tidymodels.org/.
bag_mlp( mode = "unknown", hidden_units = NULL, penalty = NULL, epochs = NULL, engine = "nnet" )
mode |
A single character string for the prediction outcome mode. Possible values for this model are "unknown", "regression", or "classification". |
hidden_units |
An integer for the number of units in the hidden model. |
penalty |
A non-negative numeric value for the amount of weight decay. |
epochs |
An integer for the number of training iterations. |
engine |
A single character string specifying what computational engine to use for fitting. |
This function only defines what type of model is being fit. Once an engine
is specified, the method to fit the model is also defined. See
set_engine()
for more on setting the engine, including how to set engine
arguments.
The model is not trained or fit until the fit()
function is used
with the data.
https://www.tidymodels.org, Tidy Modeling with R, searchable table of parsnip models
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