Setup | Data | Blocking efficiency and linkage results
Package: automatedRecLin 1.1.2
Adam Struzik
automatedRecLin: Record Linkage Based on an Entropy-Maximizing Classifier
The goal of 'automatedRecLin' is to perform record linkage (also known as entity resolution) in unsupervised or supervised settings. It compares pairs of records from two datasets using selected comparison functions to estimate the probability or density ratio between matched and non-matched records. Based on these estimates, it predicts a set of matches that maximizes entropy. For details see: Lee et al. (2022) <https://www150.statcan.gc.ca/n1/pub/12-001-x/2022001/article/00007-eng.htm>, Vo et al. (2023) <https://ideas.repec.org/a/eee/csdana/v179y2023ics0167947322002365.html>, Sugiyama et al. (2008) <doi:10.1007/s10463-008-0197-x>.
Authors:
automatedRecLin_1.1.2.tar.gz
automatedRecLin_1.1.2.zip(r-4.7)automatedRecLin_1.1.2.zip(r-4.6)automatedRecLin_1.1.2.zip(r-4.5)
automatedRecLin_1.1.2.tgz(r-4.6-any)automatedRecLin_1.1.2.tgz(r-4.5-any)
automatedRecLin_1.1.2.tar.gz(r-4.7-any)automatedRecLin_1.1.2.tar.gz(r-4.6-any)
automatedRecLin_1.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
automatedRecLin/json (API)
| # Install 'automatedRecLin' in R: |
| install.packages('automatedRecLin', repos = c('https://ncn-foreigners.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/ncn-foreigners/automatedreclin/issues
Datasets:
entity-resolutionrecord-linkage
Last updated from:a3e05d2b97. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 219 | ||
| source / vignettes | OK | 287 | ||
| linux-release-x86_64 | OK | 219 | ||
| macos-release-arm64 | OK | 165 | ||
| macos-oldrel-arm64 | OK | 125 | ||
| windows-devel | OK | 184 | ||
| windows-release | OK | 196 | ||
| windows-oldrel | OK | 198 | ||
| wasm-release | OK | 184 |
Exports:abs_distancecomparison_vectorscontrol_kliepcustom_rec_lin_modeljarowinkler_complementjoin_recordsmecmec_blockingtrain_rec_lin
Dependencies:BHbitbit64blockingclicliprcpp11crayondata.tabledensityratiodigestdqrngfarverFixedPointfloatggh4xggplot2gluegtablehmsigraphisobandlabelinglatticelgrlifecyclelpSolvemagrittrMASSMatrixMatrixExtramlapimlpacknleqslvosqppbapplypillarpkgconfigprettyunitsprogresspurrrR6RColorBrewerRcppRcppAnnoyRcppArmadilloRcppEnsmallenRcppHNSWRcppProgressreadrreclin2RhpcBLASctlrlangrnndescentrsparseS7scalessitmoSnowballCstringdiststringitext2vectibbletidyselecttokenizerstzdbutf8vctrsviridisLitevroomwithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| A_example dataset | A_example |
| Absolute Distance Comparison Function | abs_distance |
| B_example dataset | B_example |
| Fictional census data | census |
| Fictional customer data | cis |
| Create Comparison Vectors for Record Linkage | comparison_vectors |
| Controls for the kliep() Function | control_kliep |
| Create a Custom Record Linkage Model | custom_rec_lin_model |
| Jaro-Winkler Distance | jarowinkler_complement |
| Join Records Using Linkage Results | join_records |
| Unsupervised Maximum Entropy Classifier for Record Linkage | mec |
| Blocked Unsupervised Maximum Entropy Classifier for Record Linkage | mec_blocking |
| Predict Matches Based on a Given Record Linkage Model | predict.rec_lin_model |
| Train a Record Linkage Model | train_rec_lin |