fpmoutliers (version 0.1.0)

build: Automatic build of the anomaly detection model

Description

An experimental implementataion that automatically builds an anomaly detection model

Usage

build(data, func = FPI, initial_support = 0.5, top_outlier_threshold = 3,
  iteration_timeout = 10)

Arguments

data

data.frame or transactions from arules with input data

func

function name of the method that will be use during the automatic build

initial_support

initial maximum support

top_outlier_threshold

number of top unique outliers as a stopping condition

iteration_timeout

timeout of one iteration

Value

model of outlier detection

Examples

# NOT RUN {
# simple build with default parameters (FPI method)
library("fpmoutliers")
data("iris")
model <- fpmoutliers::build(iris[sample(nrow(iris), 5),])

# }
# NOT RUN {
# using other anomaly detection methods for the automatic build (e.g. LFPOF)
library("fpmoutliers")
data("iris")
model <- fpmoutliers::build(iris[sample(nrow(iris), 5),], func=LFPOF)
# }