pmml (version 1.5.4)

pmml.kmeans: Generate PMML for kmeans objects

Description

Generate the PMML representation for a kmeans object (cluster) from package stats. The kmeans object (a cluster described by k centroids) is converted into a PMML representation.

Usage

# S3 method for kmeans
pmml(model, model.name="KMeans_Model", app.name="Rattle/PMML",
     description="KMeans cluster model", copyright=NULL,
     transforms=NULL, unknownValue=NULL, 
     algorithm.name="KMeans: Hartigan and Wong", …)

Arguments

model

a kmeans object.

model.name

a name to be given to the model in the PMML code.

app.name

the name of the application that generated the PMML code.

description

a descriptive text for the Header element of the PMML code.

copyright

the copyright notice for the model.

transforms

data transformations represented in PMML via pmmlTransformations.

unknownValue

value to be used as the 'missingValueReplacement' attribute for all MiningFields.

algorithm.name

the variety of kmeans used.

…

further arguments passed to or from other methods.

Details

A kmeans object is obtained by applying the kmeans function from the stats package. This method typically requires the user to normalize all the variables, these operations can be done using the pmmlTransformations package so that the normalization information is included in the pmml model format.

References

R project: K-Means Clustering

Examples

# NOT RUN {
ds <- rbind(matrix(rnorm(100, sd = 0.3), ncol = 2),
                matrix(rnorm(100, mean = 1, sd = 0.3), ncol = 2))
colnames(ds) <- c("Dimension1", "Dimension2")
cl <- kmeans(ds, 2)
pmml(cl)

# }