Description Usage Arguments Value
Creates an object designed to be passed to init_stacker that describes an gbm3::gbmt_fit model be added to the stacking ensemble.
Creates an object designed to be passed to init_stacker that describes an xgboost::xgb.train model be added to the stacking ensemble.
1 2 3 4 5 6 7 | init_xgboost(model_name = "xgboost", arguments = list(),
params_arg = list(nthread = 1), nrounds = 10,
binomial_evaluation = "prev", weight_column = "")
init_xgboost(model_name = "xgboost", arguments = list(),
params_arg = list(nthread = 1), nrounds = 10,
binomial_evaluation = "prev", weight_column = "")
|
model_name |
name of the brt model |
arguments |
named list. Arguments to be passed to the gbm3::gbmt_fit function. Should only be used for options not captured by the params argument in the underlying xgboost function call. See help xgboost::xgb.train for more information |
params_arg |
named list. Arguments to be passed to the parameters argument of the xgboost::xgb.train function |
nrounds |
numeric. Max number of iterations |
binomial_evaluation |
one of 'prev', 'poisson', or 'emplogit'. Prev fits on indicator/N with reg:logistic evaluation. Poisson uses log(N) as an offset while modelling under a poisson. Emplogit transforms things and runs under gaussian family |
training_params |
named list. Arguments to be passed to the gbm3::training_params function |
model_name |
name of the brt model |
arguments |
named list. Arguments to be passed to the xgboost::xgb.train function. Should only be used for options not captured by the params argument in the underlying xgboost function call. See help xgboost::xgb.train for more information |
nrounds |
numeric. Max number of iterations |
binomial_evaluation |
one of 'prev', 'poisson', or 'emplogit'. Prev fits on indicator/N with reg:logistic evaluation. Poisson uses log(N) as an offset while modelling under a poisson. Emplogit transforms things and runs under gaussian family |
named list of lists with the parameters required to run an brt model
named list of lists with the parameters required to run an brt model
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