logicDT.bagging {logicDT}

Fitting bagged logicDT models

Description

Function for fitting bagged logicDT models.

Usage

## Default S3 method:
logicDT.bagging(X, y, Z = NULL, bagging.iter = 500, ...)

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

Arguments

X

Matrix or data frame of binary predictors coded as 0 or 1.

y

Response vector. 0-1 coding for binary responses. Otherwise, a regression task is assumed.

Z

Optional matrix or data frame of quantitative/continuous covariables. Multiple covariables allowed for splitting the trees. If leaf regression models (such as four parameter logistic models) shall be fitted, only the first given covariable is used.

bagging.iter

Number of bagging iterations

...

Arguments passed to logicDT

formula

An object of type formula describing the model to be fitted.

data

A data frame containing the data for the corresponding formula object. Must also contain quantitative covariables if they should be included as well.

Details

Details on single logicDT models can be found in logicDT.

Value

An object of class logic.bagged. This is a list containing

models

A list of fitted logicDT models

bags

A list of observation indices which were used to train each model

...

Supplied parameters of the functional call to logicDT.bagging.