Understanding the RLdata500 dataset | Preparing the data | Setting the Tuning Parameters | The Gibbs Sampler for bLink | Summary information of blink
Package: blink 1.1.0
Rebecca Steorts
blink: Record Linkage for Empirically Motivated Priors
An implementation of the model in Steorts (2015) <doi:10.1214/15-BA965SI>, which performs Bayesian entity resolution for categorical and text data, for any distance function defined by the user. In addition, the precision and recall are in the package to allow one to compare to any other comparable method such as logistic regression, Bayesian additive regression trees (BART), or random forests. The experiments are reproducible and illustrated using a simple vignette. LICENSE: GPL-3 + file license.
Authors:
blink_1.1.0.tar.gz
blink_1.1.0.zip(r-4.7)blink_1.1.0.zip(r-4.6)blink_1.1.0.zip(r-4.5)
blink_1.1.0.tgz(r-4.6-any)blink_1.1.0.tgz(r-4.5-any)
blink_1.1.0.tar.gz(r-4.7-any)blink_1.1.0.tar.gz(r-4.6-any)
blink_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
blink/json (API)
| # Install 'blink' in R: |
| install.packages('blink', repos = c('https://cleanzr.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/cleanzr/blink/issues
Datasets:
- identity.RLdata500 - Identity.RLdata500
- RLdata500 - RLdata500
Last updated from:7aae7e9dbb. Checks:7 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | NOTE | 124 | ||
| source / vignettes | OK | 156 | ||
| linux-release-x86_64 | NOTE | 117 | ||
| macos-release-arm64 | NOTE | 91 | ||
| macos-oldrel-arm64 | NOTE | 119 | ||
| windows-devel | NOTE | 82 | ||
| windows-release | NOTE | 72 | ||
| windows-oldrel | NOTE | 66 | ||
| wasm-release | OK | 109 |
Exports:check_IDslinkslinks.comparemmsmpmmspairwiserl.gibbs
Dependencies:plyrRcppstringdist
