MFPOF: MFPOF algorithm

In fpmoutliers: Frequent Pattern Mining Outliers

Description

Algorithm proposed by: Feng Lin, Wang Le, Jin Bo - Research on Maximal Frequent Pattern Outlier Factor for Online HighDimensional Time-Series Outlier Detection. Journal of Convergence Information Technology 5(10):66-71. December 2010.

Usage

MFPOF(data, minSupport = 0.3, mlen = 0, noCores = 1)

Arguments

data	data.frame or transactions from arules with input data
minSupport	minimum support for FPM
mlen	maximum length of frequent itemsets
noCores	number of cores for parallel computation

Value

model output (list) with all results including outlier scores

Examples

library("fpmoutliers")
dataFrame <- read.csv(
     system.file("extdata", "fp-outlier-customer-data.csv", package = "fpmoutliers"))
model <- MFPOF(dataFrame, minSupport = 0.001)

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