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corkscrew (version 1.1)

apply.tbin: Extrapolate t-test based binning to a new data

Description

Extrapolates the binning of categorical variables to the new datasets.

Usage

apply.tbin(idv, train.output, test)

Arguments

idv
Predictor variables in the dataframe which are categorical and need to be binned.
train.output
The output object of the tbin function.
test
A new data set on which binning has to be extrapolated.

Value

Returns a dataframe which contains the extrapolated variables of the output object from tbin function appended to the new dataset.

Warning

New level error is thrown if the new dataset contains new levels other than what is present in the old dataset.

Details

This function performs binning on the new dataset based on the output object from the tbin function.

See Also

tbin, ctoc, apply.ctoc.

Examples

Run this code
train = as.data.frame(cbind(runif(1000, 10, 1000),sample(1:40, 1000,TRUE)))
colnames(train) = c("response","state")
train$state = as.factor(train$state)
train.output = tbin(dv = "response",idv = c("state"),train,25,TRUE)

# extrapolating the tbin function to a new dataset using apply.tbin
test = as.data.frame(sample(1:40, 100,TRUE))
colnames(test) = c("state")
test$state = as.factor(test$state)
test.output = apply.tbin(idv = c("state"), train.output, test)

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