Package: ldbod 0.1.2
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.
Authors:
ldbod_0.1.2.tar.gz
ldbod_0.1.2.zip(r-4.7-any)ldbod_0.1.2.zip(r-4.6-any)ldbod_0.1.2.zip(r-4.5-any)
ldbod_0.1.2.tgz(r-4.6-any)ldbod_0.1.2.tgz(r-4.5-any)
ldbod_0.1.2.tar.gz(r-4.7-any)ldbod_0.1.2.tar.gz(r-4.6-any)
ldbod_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
ldbod/json (API)
| # Install 'ldbod' in R: |
| install.packages('ldbod', repos = c('https://kwilliams83.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/kwilliams83/ldbod/issues
Last updated from:a93a70c7db. Checks:9 OK. Indexed: yes.
