cocktailEnsemble: Cocktail Ensemble: build a model consisting of multiple...

Description Usage Arguments Value Author(s) References See Also Examples

View source: R/cocktailEnsemble.R

Description

cocktailEnsemble is a classification algorithm. It builds four models by calling glm (logit), kernelFactory, randomForest, and ada.

Usage

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Arguments

x

A data frame containing the predictors.

y

The response vector.

Value

An object of type cocktailEnsemble containing the four aforementioned models.

Author(s)

Dirk Van den Poel, Michel Ballings, Andrey Volkov, Jeroen D”haen, Michiel Van Herwegen

Maintainer: Michel Ballings <Michel.Ballings@GMail.com>

References

Van den Poel, D., Ballings, M., Volkov, A., D”haen, J., Vanherwegen, M., Predictive Analytics for analytical Customer Relationship Management using SAS, Oracle and R, Springer, Forthcoming.

glm:

randomForest:

kernelFactory:

ada:

See Also

Other functions in this package: imputeMissings, Aggregate, cocktailEnsemble, predict.cocktailEnsemble

Examples

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#Credit Approval data available at UCI Machine Learning Repository
data(Credit)

#Create training set (take a small subset for demonstration purposes)
Credit <- data.frame(Credit[order(runif(nrow(Credit ))),])[1:100,c('V2','V3','V8','V11','V14','V15','Response')]
trainingset <- Credit[1:1:floor(0.50*nrow(Credit)),]
#Create test set
#testset <- Credit[(floor(0.50*nrow(Credit))+1 ):nrow(Credit),]


#Train Cocktail Ensemble on training data
cE <- cocktailEnsemble(x=trainingset[,names(trainingset)!= "Response"],y=trainingset$Response)

#Deploy Kernel Factory to predict response for test data
#pred <- predict(cE,testset[,names(testset)!= "Response"])

aCRM documentation built on May 19, 2017, 8:24 a.m.

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