Package: matchFeat 1.0

matchFeat: One-to-One Feature Matching

Statistical methods to match feature vectors between multiple datasets in a one-to-one fashion. Given a fixed number of classes/distributions, for each unit, exactly one vector of each class is observed without label. The goal is to label the feature vectors using each label exactly once so to produce the best match across datasets, e.g. by minimizing the variability within classes. Statistical solutions based on empirical loss functions and probabilistic modeling are provided. The 'Gurobi' software and its 'R' interface package are required for one of the package functions (match.2x()) and can be obtained at <https://www.gurobi.com/> (free academic license). For more details, refer to Degras (2022) <doi:10.1080/10618600.2022.2074429> "Scalable feature matching for large data collections" and Bandelt, Maas, and Spieksma (2004) <doi:10.1057/palgrave.jors.2601723> "Local search heuristics for multi-index assignment problems with decomposable costs".

Authors:David Degras

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matchFeat/json (API)

# Install 'matchFeat' in R:
install.packages('matchFeat', repos = c('https://ddegras.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 3 scripts 202 downloads 10 exports 5 dependencies

Last updated 2 years agofrom:9c76900d9a. Checks:1 OK, 8 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 08 2025
R-4.5-winNOTEMar 08 2025
R-4.5-macNOTEMar 08 2025
R-4.5-linuxNOTEMar 08 2025
R-4.4-winNOTEMar 08 2025
R-4.4-macNOTEMar 08 2025
R-4.4-linuxNOTEMar 08 2025
R-4.3-winNOTEMar 08 2025
R-4.3-macNOTEMar 08 2025

Exports:match.2xmatch.bcamatch.bca.genmatch.gaussmixmatch.kmeansmatch.recmatch.templateobjective.funobjective.gen.funRand.index

Dependencies:clueclustercodetoolsforeachiterators