generatePMML: PMML conversion - PMML representation of outliers

In fpmoutliers: Frequent Pattern Mining Outliers

Description

Kuchar, Jaroslav et al. “Outlier (Anomaly) Detection Modelling in PMML.” RuleML+RR (2017).(http://ceur-ws.org/Vol-1875/paper9.pdf)

Usage

generatePMML(model, dataFrame = NULL, topN = NULL)

Arguments

model	outlier model
dataFrame	frame for labeling
topN	limit number of outliers in the output

Value

pmml model

Examples

## Not run: 
library("fpmoutliers")
dataFrame <- read.csv(
     system.file("extdata", "fp-outlier-customer-data.csv", package = "fpmoutliers"))
model <- FPI(dataFrame, minSupport = 0.001)
generatePMML(model, dataFrame)

## End(Not run)

fpmoutliers documentation built on May 2, 2019, 8:53 a.m.