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library(sqlrutils) # Contains the utiity that lets us create a stored procedure automatically from R code | |
buildCustomerTree <- function(trainingDs) { | |
# | |
# Make factors out of these numbers otherwise they get treated as continuos values | |
# | |
trainingDs$TotalChildren <- as.factor(trainingDs$TotalChildren) | |
trainingDs$NumberChildrenAtHome <- as.factor(trainingDs$NumberChildrenAtHome) | |
trainingDs$NumberCarsOwned <- as.factor(trainingDs$NumberCarsOwned) | |
trainingDs$YearsSinceFirstPurchase <- as.factor(trainingDs$YearsSinceFirstPurchase) | |
trainingDs$AgeRanges <- cut( | |
trainingDs$Age,breaks=c(0,30,50,70,90), | |
labels=c("11-30","31-50","51-70","71+") | |
) | |
trainingDs$IncomeCategories <- cut( | |
x=trainingDs$YearlyIncome, | |
breaks=c(0,20000,50000,70000,100000,250000), | |
labels=c("Low","Lower","Middle","Upper","Wealthy") | |
) | |
tr <- rxDTree( | |
IsCardUser~ | |
Gender+ | |
Occupation+ | |
MaritalStatus+ | |
IsHomeOwner+ | |
TotalChildren+ | |
NumberCarsOwned+ | |
AgeRanges+ | |
CommuteDistance+ | |
IncomeCategories+ | |
CountryRegionCode+ | |
Education, | |
data=trainingDs, | |
method="class", | |
overwrite = TRUE, | |
reportProgress = 0, | |
cp = 0.03 | |
) | |
trained_model <- rxSerializeModel(tr) | |
return(list(trained_model=trained_model)) | |
} |
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