logforest: Logic Forest

In LogicForest: Logic Forest

Logic Forest

Description

Constructs an ensemble of logic regression models using bagging for classification and identification of important predictors and predictor interactions

Usage

logforest(resp, Xs, nBSXVars, anneal.params, nBS=100, h=0.5, norm=TRUE, numout=5, nleaves)

Arguments

resp	numeric vector of binary response values
Xs	matrix or dataframe of zeros and ones for all predictor variables
nBSXVars	integer for the number of predictors used to construct each logic regression model. The default value is all predictors in the data.
anneal.params	a list containing the parameters for simulated annealing. See the help file for the function logreg.anneal.control in the LogicReg package. If missing, default annealing parameters are set at start=1, end=-2, and iter=50000.
nBS	number of logic regression trees to be fit in the logic forest model.
h	a number between 0 and 1 for the minimum proportion of trees in the logic forest that must predict a 1 for the prediction to be one.
norm	logical. If FALSE, predictor and interaction scores in model output are not normalized to range between zero and one.
numout	number of predictors and interactions to be included in model output
nleaves	the maximum number of end nodes generated for each tree

Value

An object of class "logforest" including a list of values

LogicForest documentation built on June 22, 2024, 7:05 p.m.