Description Usage Arguments Value Examples
xg_gs
use coordinate descent
(https://en.wikipedia.org/wiki/Coordinate_descent) in order
to select the best set of parameters for an xgboost model. At the end
of the coordinate descent algorithm, a full search on each of the
individual parameter vectors is made in order to potentially improve
the selection.
1 2 3 4 5 | xg_gs(data, eta = c(0.05, 0.1, 0.15, 0.2, 0.25, 0.3), gamma = c(0, 0.1,
0.2, 0.3, 0.4, 0.5), max_depth = c(1, 3, 4, 5, 6, 8, 10, 12, 15),
colsample_bytree = c(0.3, 0.4, 0.5, 0.7, 0.8, 0.9, 1),
min_child_weight = c(1, 3, 5, 7), nrounds = 100, nthread = 2,
cv = 5, seed = 1, verbose = TRUE, objective = "auto")
|
data |
Object. A data structure created by the call of the xg_load_data function. |
eta |
Numeric Vectors. Eta parameter list for grid search. See xgb.train for more details. |
gamma |
Numeric Vector. Gamma parameter list for grid search. See xgb.train for more details. |
max_depth |
Numeric Vector. Max_depth parameter list for grid search. See xgb.train for more details. |
colsample_bytree |
Numeric Vector. Colsample_bytree parameter list for grid search. See xgb.train for more details. |
min_child_weight |
Numeric Vector. Min_child_weight parameter list for grid search. See xgb.train for more details. |
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. |
verbose |
Logical. Verbose parameter for grid search. |
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. |
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.
1 2 3 4 5 6 | 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_gs(d)
|
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