ldbod

Local Density-Based Outlier Detection

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.

Total

6,810

Last month

468

Last week

99

Average per day

16

Daily downloads

Total downloads

Description file content

Package
ldbod
Type
Package
Title
Local Density-Based Outlier Detection
Version
0.1.2
Author
Kristopher Williams
Maintainer
Kristopher Williams
Description
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.
Depends
R (>= 3.2.0)
Imports
stats, RANN, mnormt
License
GPL-3
URL
LazyData
TRUE
RoxygenNote
6.0.1
NeedsCompilation
no
Packaged
2017-05-26 03:52:35 UTC; kwilliams
Repository
CRAN
Date/Publication
2017-05-26 06:04:25 UTC

install.packages('ldbod')

0.1.2

02 years ago

https://github.com/kwilliams83/ldbod

Kristopher Williams

GPL-3

Depends on

R (>= 3.2.0)

Imports

stats, RANN, mnormt

Discussions