fpmoutliers (version 0.1.0)

LFPOF: LFPOF algorithm

Description

Algorithm proposed by: W. Zhang, J. Wu and J. Yu, "An Improved Method of Outlier Detection Based on Frequent Pattern," Information Engineering (ICIE), 2010 WASE International Conference on, Beidaihe, Hebei, 2010, pp. 3-6.

Usage

LFPOF(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

# NOT RUN {
library("fpmoutliers")
dataFrame <- read.csv(
     system.file("extdata", "fp-outlier-customer-data.csv", package = "fpmoutliers"))
model <- LFPOF(dataFrame, minSupport = 0.001)
# }