RWBP: Detects spatial outliers using a Random Walk on Bipartite Graph
Version 1.0

a Bipartite graph and is constructed based on the spatial and/or non-spatial attributes of the spatial objects in the dataset. Secondly, RW techniques are utilized on the graphs to compute the outlierness for each point (the differences between spatial objects and their spatial neighbours). The top k objects with higher outlierness are recognized as outliers.

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AuthorSigal Shaked & Ben Nasi
Date of publication2014-06-24 23:30:50
MaintainerSigal Shaked <shaksi@post.bgu.ac.il>
LicenseGPL (>= 2)
Version1.0
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("RWBP")

Man pages

predict.RWBP: predict.RWBP
RWBP: Random Walk on Bipartite Graph
RWBP-package: Random Walk on Bipartite Graph

Functions

RWBP Man page Source code
RWBP-package Man page
RWBP.default Man page Source code
RWBP.formula Man page Source code
plot.RWBP Man page Source code
predict.RWBP Man page Source code
print.RWBP Man page Source code

Files

NAMESPACE
R
R/RW-BP-internal.R
R/RWBP.R
R/plot.RWBP.R
R/RWBP.default.R
R/RWBP.formula.R
R/predict.RWBP.R
R/print.RWBP.R
MD5
DESCRIPTION
man
man/RWBP-package.Rd
man/predict.RWBP.Rd
man/RWBP.Rd
RWBP documentation built on May 19, 2017, 9:20 p.m.