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Fit a Generalized Boosted Regression Model

fit_gbm.Rd

A wrapper for fitting boosted binary regression models for binary classification problems. Assumes a binary "Response" in [0, 1].

Usage

fit_gbm(x, ...)

# Default S3 method
fit_gbm(x, y, ...)

# S3 method for class 'formula'
fit_gbm(formula, data, ...)

Arguments

x

A data.frame containing feature data (predictors). If using the formula method, a "Response" column should be included. The simplest way to achieve this is a call to create_train().

...

Arguments passed to gbm::gbm().

y

factor(n). If not passing a formula, a factor with true class names for each sample (row) in x.

formula

A model formula of the form: \(class ~ x1 + x2 + ...+ xn`\), (no interactions).

data

A data frame of predictors (categorical and/or numeric).

Value

A gbm class object, as returned by gbm::gbm().

Methods (by class)

  • fit_gbm(default): The S3 default method for fit_gbm.

  • fit_gbm(formula): The S3 formula method for fit_gbm.

See also

gbm::gbm(), create_train()

The fit*() family: fit_kknn(), fit_logistic(), fit_nb()

Author

Stu Field

Examples

# formula method
model <- withr::with_seed(10, fit_gbm(Species ~ ., data = tr_iris))
#> Distribution not specified, assuming bernoulli ...

# data frame method
model <- withr::with_seed(10, fit_gbm(tr_iris[, -5L], y = tr_iris$Species))
#> Distribution not specified, assuming bernoulli ...