LogicForest: Logic Forest

Two classification ensemble methods based on logic regression models. LogForest uses a bagging approach to construct an ensemble of logic regression models. LBoost uses a combination of boosting and cross-validation to construct an ensemble of logic regression models. Both methods are used for classification of binary responses based on binary predictors and for identification of important variables and variable interactions predictive of a binary outcome.

Install the latest version of this package by entering the following in R:
install.packages("LogicForest")
AuthorBethany Wolf
Date of publication2014-09-19 00:46:31
MaintainerBethany Wolf <wolfb@musc.edu>
LicenseGPL-2
Version2.1.0

View on CRAN

Man pages

ada.pred: Internal Logic Forest Functions

ada.weights: Internal Logic Forest Functions

BoostVimp.plot: Variable and Interaction Importance Plots for a LBoost Model

CV.data: Internal Logic Forest Functions

CV.err: Internal Logic Forest Functions

CV.ids: Internal Logic Forest Functions

LBoost: LBoost

LBoost.fit: Example of a LBoost Model

LBoost.PIs: Internal Logic Forest Functions

LF.data: Example Data for Logic Forest and LBoost

LF.testdata: Example of New Test Data for Prediction in Logic Forest and...

list.PIs: Internal Logic Forest Functions

logforest: Logic Forest

logforest.fit: Example of a Logic Forest Model

LogicForest-package: Logic Forest

p.combos: Internal Logic Forest Functions

Perm.PIimp: Internal Logic Forest Functions

Perms: Internal Logic Forest Functions

persistence.plot: Plot Persistence of a Variable of Interaction

persistence.prep: Internal Logic forest Functions

persist.match: Internal Logic Forest Functions

pimp.import: Internal Logic Forest Functions

pimp.mat: Internal Logic Forest Functions

PlusMinus.PIimp: Internal Logic Forest Functions

predict.LBoost: Prediction of Response Using LBoost

predict.logforest: Prediction of Response Using Logic Forest

Pred.imp: Internal Logic Forest Functions

prime.imp: Internal Logic Forest Functions

print.LBoost: Prints Output for and LBoost Model

print.LFprediction: Prints Logic Forest Prediction Output

print.logforest: Prints Output for a Logic Forest Model

proportion.positive: Internal Logic Forest Functions

submatch.plot: Plot of Variable/Interaction Frequency

subs: Internal Logic Forest Functions

TTab: Internal Logic Forest Functions

vimp.plot: Variable and Interaction Importance Plots for a Logic Forest...

Functions

ada.pred Man page
ada.weights Man page
BoostVimp.plot Man page
CV.data Man page
CV.err Man page
CV.ids Man page
LBoost Man page
LBoost.fit Man page
LBoost.PIs Man page
LF.data Man page
LF.testdata Man page
list.PIs Man page
logforest Man page
logforest.fit Man page
LogicForest Man page
LogicForest-package Man page
p.combos Man page
Perm.PIimp Man page
Perms Man page
persistence.plot Man page
persistence.prep Man page
persist.match Man page
pimp.import Man page
pimp.mat Man page
PlusMinus.PIimp Man page
predict.LBoost Man page
predict.logforest Man page
Pred.imp Man page
prime.imp Man page
print.LBoost Man page
print.LFprediction Man page
print.logforest Man page
proportion.positive Man page
submatch.plot Man page
subs Man page
TTab Man page
vimp.plot Man page

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