xgb_params: XGboost Parameters

In creditmodel: Toolkit for Credit Modeling, Analysis and Visualization

Description

xgb_params is the list of parameters to train a XGB model using in training_model. xgb_params_search is for searching the optimal parameters of xgboost,if any parameters of params in xgb_params is more than one.

Usage

xgb_params(
  nrounds = 1000,
  params = list(max_depth = 6, eta = 0.01, gamma = 0, min_child_weight = 1, subsample =
    1, colsample_bytree = 1, scale_pos_weight = 1),
  early_stopping_rounds = 100,
  method = "random_search",
  iters = 10,
  f_eval = "auc",
  nfold = 1,
  nthread = 2,
  ...
)

xgb_params_search(
  dat_train,
  target,
  dat_test = NULL,
  x_list = NULL,
  prop = 0.7,
  occur_time = NULL,
  method = "random_search",
  iters = 10,
  nrounds = 100,
  early_stopping_rounds = 10,
  params = list(max_depth = 6, eta = 0.01, gamma = 0, min_child_weight = 1, subsample =
    1, colsample_bytree = 1, scale_pos_weight = 1),
  f_eval = "auc",
  nfold = 1,
  nthread = 2,
  ...
)

Arguments

nrounds	Max number of boosting iterations.
params	List of contains parameters of xgboost. The complete list of parameters is available at: http://xgboost.readthedocs.io/en/latest/parameter.html
early_stopping_rounds	If NULL, the early stopping function is not triggered. If set to an integer k, training with a validation set will stop if the performance doesn't improve for k rounds.
method	Method of searching optimal parameters."random_search","grid_search","local_search" are available.
iters	Number of iterations of "random_search" optimal parameters.
f_eval	Custimized evaluation function,"ks" & "auc" are available.
nfold	Number of the cross validation of xgboost
nthread	Number of threads
...	Other parameters
dat_train	A data.frame of train data. Default is NULL.
target	Name of target variable.
dat_test	A data.frame of test data. Default is NULL.
x_list	Names of independent variables. Default is NULL.
prop	Percentage of train-data after the partition. Default: 0.7.
occur_time	The name of the variable that represents the time at which each observation takes place.Default is NULL.

Value

A list of parameters.

See Also

training_model, lr_params,gbm_params, rf_params

creditmodel documentation built on Jan. 7, 2022, 5:06 p.m.