xg_bo: Bayesian Optimization

In ArnaudBu/ezXg: Easy xbgoost wrapper

Description

xg_bo use the bayesian optimization algorithm implemented in the rBayesianOptimization package in order to select the best set of parameters for an xgboost model.

Usage

xg_bo(data, eta = c(0.05, 0.3), gamma = c(0, 0.5), max_depth = c(1L,
  15L), colsample_bytree = c(0.5, 1), min_child_weight = c(1L, 7L),
  nrounds = 100, nthread = 2, cv = 5, seed = 1,
  objective = "auto", init_grid_dt = NULL, kernel = list(type =
  "exponential", power = 2), init_points = 10, n_iter = 50,
  acq = "ucb", kappa = 2.576, eps = 0, verbose = TRUE)

Arguments

data	Object. A data structure created by the call of the xg_load_data function.
eta	Numeric Vectors. Eta parameter min and max bounds.
gamma	Numeric Vector. Gamma parameter min and max bounds.
max_depth	Numeric Vector. Max_depth parameter min and max bounds. Use "L" suffix to indicate integer hyperparameter.
colsample_bytree	Numeric Vector. Colsample_bytree parameter min and max bounds.
min_child_weight	Numeric Vector. Min_child_weight parameter min and max bounds. Use "L" suffix to indicate integer hyperparameter.
nrounds	Numeric. Nrounds parameter for xgboost calibration. See xgb.train for more details.
nthread	Numeric. Nthread parameter for xgboost calibration. See xgb.train for more details.
cv	Numeric. Number of folds in cross validation. Needs to be more than 2.
seed	Numeric. Seed for computation reproducability.
objective	Character. Objective function for the optimization. . Eta parameter for xgboost calibration. See xgb.train for more details. Can be set to auto in order to let the function choose the better model regarding the output variable.
verbose	Logical. Verbose parameter for grid search.
...	Other parameters from BayesianOptimization.

Value

The optimization results with the following fields:

• param: the optimal set of parameters.

• err: the error associated to the optimal parameter set.

• results: the history of the results for the cross-validation with all the tested sets of parameters.

Examples

d <- xg_load_data(system.file("extdata", "titanic.csv", package = "ezXg"),
               inputs = c("Pclass", "Sex", "Age", "SibSp",
                          "Parch", "Fare", "Embarked"),
               output = "Survived",
               train.size = 0.8)
t <- xg_bo(d)

ArnaudBu/ezXg documentation built on Oct. 30, 2019, 4:59 a.m.