gb_classifier applies gradient boosting classification to a data set.
gb_classifier(
y,
form,
distribution,
data.train,
n.trees,
interaction.depth,
n.minobsinnode,
shrinkage,
verbose = c(TRUE, FALSE)
)A gradient tree boosting model. A gbm object.
Outcome variable. A character vector containing the column names of
the outcome variable. A character scalar containing the column name of
the outcome variable in survey.
Model formula. A two-sided linear formula describing the model to be fit, with the outcome on the LHS and the covariates separated by + operators on the RHS.
Model distribution. A character string specifying the name of the distribution to be used.
Training data. A data.frame containing the training data used to train the model.
Total number of trees. An integer-valued scalar specifying the total number of trees to be fit.
Interaction depth. An integer-valued scalar specifying the maximum depth of each tree.
Minimum number of observations in terminal nodes. An integer-valued scalar specifying the minimum number of observations in the terminal nodes of the trees.
Learning rate. A numeric scalar specifying the shrinkage or learning rate applied to each tree in the expansion.
Verbose output. A logical vector indicating whether or not verbose output should be printed.