ldbod: Local Density-Based Outlier Detection
Version 0.1.1

Flexible procedures to compute local density-based outlier scores for ranking outliers. Both exact and approximate nearest neighbor search can be implemented, while also accommodating multiple neighborhood sizes and four different local density-based methods. It allows for referencing a random subsample of the input data or a user specified reference data set to compute outlier scores against, so both unsupervised and semi-supervised outlier detection can be implemented.

AuthorKristopher Williams
Date of publication2016-12-22 09:04:34
MaintainerKristopher Williams <kristopher.williams83@gmail.com>
LicenseGPL-3
Version0.1.1
URL https://github.com/kwilliams83/ldbod
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("ldbod")

Getting started

README.md

Popular man pages

ldbod: Local Density-Based Outlier Detection using Subsampling with...
ldbod.ref: Local Density-Based Outlier Detection using Reference Data...
See all...

All man pages Function index File listing

Man pages

ldbod: Local Density-Based Outlier Detection using Subsampling with...
ldbod.ref: Local Density-Based Outlier Detection using Reference Data...

Functions

ldbod Man page Source code
ldbod.ref Man page Source code

Files

NAMESPACE
R
R/ldbod.R
R/ldbod.ref.R
README.md
MD5
DESCRIPTION
man
man/ldbod.ref.Rd
man/ldbod.Rd
ldbod documentation built on May 19, 2017, 6:11 p.m.