logicDT.bagging: Fitting bagged logicDT models

In logicDT: Identifying Interactions Between Binary Predictors

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 four parameter logistic models shall be fitted in the leaves, 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 observations indices which were used to train each model
...	Supplied parameters of the functional call to logicDT.bagging.

logicDT documentation built on Jan. 14, 2023, 5:06 p.m.