The stop_iter()
argument allows the model to prematurely stop training if the objective function does not improve within early_stop
iterations.
The best way to use this feature is in conjunction with an internal validation set. To do this, pass the validation
parameter of \code{\link[=xgb_train]{xgb_train()}} via the parsnip \code{\link[=set_engine]{set_engine()}} function. This is the proportion of the training set that should be reserved for measuring performance (and stopping early).
If the model specification has early_stop >= trees
, early_stop
is converted to trees - 1
and a warning is issued.
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