FPOF: FPOF - Frequent Pattern Outlier Factor algorithm

Description Usage Arguments Value Examples

Description

Algorithm proposed by: He, Z., Xu, X., Huang, J. Z., Deng, S.: FP-Outlier: Frequent Pattern Based Outlier Detection. Computer Science and Information Systems, Vol. 2, No. 1, 103-118. (2005)

Usage

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FPOF(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

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

jaroslav-kuchar/fpmoutliers documentation built on May 18, 2019, 4:48 p.m.