Especificacao de gradient boosting
Usage
rnp_ml_boosting(
modo = c("classificacao", "regressao"),
arvores = 500,
profundidade = 6,
taxa_aprendizado = 0.1
)
Arguments
- modo
"classificacao" ou "regressao".
- arvores
Numero de arvores.
- profundidade
Profundidade das arvores.
- taxa_aprendizado
Taxa de aprendizado.
Value
Especificacao model_spec (engine xgboost).
See also
Other ml:
rnp_ml_ajustar(),
rnp_ml_arvore(),
rnp_ml_comparar(),
rnp_ml_cv(),
rnp_ml_floresta(),
rnp_ml_importancia(),
rnp_ml_knn(),
rnp_ml_particao(),
rnp_ml_prever(),
rnp_ml_receita(),
rnp_ml_regularizada(),
rnp_ml_svm(),
rnp_ml_tunagem()
Examples
rnp_ml_boosting("regressao")
#> Boosted Tree Model Specification (regression)
#>
#> Main Arguments:
#> trees = 500
#> tree_depth = 6
#> learn_rate = 0.1
#>
#> Computational engine: xgboost
#>