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knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
library(LogicForest) library(data.table) library(LogicReg)
load(system.file("data", "LF.data.rda", package="LogicForest")) data(LF.data) #Set using annealing parameters using the logreg.anneal.control #function from LogicReg package newanneal<-logreg.anneal.control(start=1, end=-2, iter=2500) #typically more than 2500 iterations (iter>25000) would be used for #the annealing algorithm. A typical forest also contains at #least 100 trees. These parameters were set to allow for faster #run times #The data set LF.data contains 50 binary predictors and a binary #response Ybin LF.fit1<-logforest(resp=LF.data$Ybin, Xs=LF.data[,1:50], nBS=20, anneal.params=newanneal) print(LF.fit1) predict(LF.fit1) #Changing print parameters LF.fit2<-logforest(resp=LF.data$Ybin, Xs=LF.data[,1:50], nBS=20, anneal.params=newanneal, norm=TRUE, numout=10) print(LF.fit2)
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