B_example

<p>An example dataset containing artificial personal data.</p>

datasets

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>.

Adam Struzik

automatedRecLin

Record Linkage Based on an Entropy-Maximizing Classifier

Maciej Beręsewicz

B_example function

<p>A <code>data.frame</code> with 12 records. Each row represents one record, with the following columns:
<code>name</code>, <code>surname</code>, and <code>city</code>. Some records can be matched with records in the
<code>A_example</code> dataset.</p>

B_example: B_example dataset

Description

Usage

Arguments

Format

Examples