{ "_id": "6a17fc4cacfb0bcc41daa5c4", "Package": "matchFeat", "Type": "Package", "Title": "One-to-One Feature Matching", "Version": "1.0", "Date": "2022-12-10", "Author": "David Degras", "Maintainer": "David Degras ", "Description": "Statistical methods to match feature vectors between\nmultiple datasets in a one-to-one fashion. Given a fixed number\nof classes/distributions, for each unit, exactly one vector of\neach class is observed without label. The goal is to label the\nfeature vectors using each label exactly once so to produce the\nbest match across datasets, e.g. by minimizing the variability\nwithin classes. Statistical solutions based on empirical loss\nfunctions and probabilistic modeling are provided. The 'Gurobi'\nsoftware and its 'R' interface package are required for one of\nthe package functions (match.2x()) and can be obtained at\n (free academic license). For more\ndetails, refer to Degras (2022)\n \"Scalable feature matching\nfor large data collections\" and Bandelt, Maas, and Spieksma\n(2004) \"Local search\nheuristics for multi-index assignment problems with\ndecomposable costs\".", "License": "GPL-2", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-28 08:23:40 UTC", "User": "root" }, "Repository": "https://ddegras.r-universe.dev", "Date/Publication": "2022-12-13 11:30:07 UTC", "RemoteUrl": "https://github.com/cran/matchFeat", "RemoteRef": "HEAD", "RemoteSha": "9c76900d9a83397c30d5bc607dddd70da8e53529", "MD5sum": "a3f4340de73ce3d8ead507ec3e112aa1", "_user": "ddegras", "_type": "src", "_file": "matchFeat_1.0.tar.gz", "_fileid": "7d633da829cd998cdac2bd284613af78c0ec8e05f494187bd8242f812b8cbc21", "_filesize": 292863, "_sha256": "7d633da829cd998cdac2bd284613af78c0ec8e05f494187bd8242f812b8cbc21", "_created": "2026-05-28T08:23:40.000Z", "_published": "2026-05-28T08:26:52.329Z", "_distro": "noble", "_jobs": [ { "job": 78252164778, "time": 109, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "NOTE", "artifact": "7261146762" }, { "job": 78252164750, "time": 143, "config": "linux-release-x86_64", "r": "4.6.0", "check": "NOTE", "artifact": "7261157543" }, { "job": 78252164823, "time": 150, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "NOTE", "artifact": "7261147694" }, { "job": 78252164740, "time": 154, "config": "macos-release-arm64", "r": "4.6.0", "check": "NOTE", "artifact": "7261151971" }, { "job": 78251731610, "time": 164, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7261109244" }, { "job": 78252164840, "time": 90, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7261140179" }, { "job": 78252164800, "time": 96, "config": "windows-devel", "r": "4.7.0", "check": "NOTE", "artifact": "7261150860" }, { "job": 78252164797, "time": 90, "config": "windows-oldrel", "r": "4.5.3", "check": "NOTE", "artifact": "7261150674" }, { "job": 78252164760, "time": 63, "config": "windows-release", "r": "4.6.0", "check": "NOTE", "artifact": "7261131271" } ], "_buildurl": "https://github.com/r-universe/ddegras/actions/runs/26563364102", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/cran/matchFeat", "_commit": { "id": "9c76900d9a83397c30d5bc607dddd70da8e53529", "author": "David Degras ", "committer": "cran-robot ", "message": "version 1.0\n", "time": 1670931007 }, "_maintainer": { "name": "David Degras", "email": "david.degras@umb.edu", "login": "ddegras", "description": "", "uuid": 6077672 }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 3.5.0", "role": "Depends" }, { "package": "clue", "role": "Imports" }, { "package": "foreach", "role": "Imports" }, { "package": "methods", "role": "Imports" }, { "package": "utils", "role": "Imports" }, { "package": "gurobi", "role": "Suggests" } ], "_owner": "cran", "_selfowned": true, "_usedby": 0, "_updates": [], "_tags": [], "_stars": 0, "_contributors": [ { "user": "ddegras", "count": 1, "uuid": 6077672 } ], "_userbio": { "uuid": 6077672, "type": "user", "name": "David Degras" }, "_downloads": { "count": 186, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/matchFeat" }, "_searchresults": 3, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/matchFeat.html", "manual.pdf" ], "_realowner": "ddegras", "_cranurl": false, "_releases": [ { "version": "1.0", "date": "2022-12-13" } ], "_exports": [ "match.2x", "match.bca", "match.bca.gen", "match.gaussmix", "match.kmeans", "match.rec", "match.template", "objective.fun", "objective.gen.fun", "Rand.index" ], "_datasets": [ { "name": "optdigits", "title": "Handwritten Digits Data", "object": "optdigits", "file": "optdigits.rda", "class": [ "list" ], "fields": [], "table": false, "tojson": true } ], "_help": [ { "page": "matchFeat-package", "title": "One-to-One Feature Matching", "topics": [ "matchFeat-package" ] }, { "page": "match.2x", "title": "Pairwise Interchange Heuristic (2-Assignment-Exchange)", "topics": [ "match.2x" ] }, { "page": "match.bca", "title": "Block Coordinate Ascent Method", "topics": [ "match.bca" ] }, { "page": "match.bca.gen", "title": "Block Coordinate Ascent Method for General (Balanced or Unbalanced) Data", "topics": [ "match.bca.gen" ] }, { "page": "match.gaussmix", "title": "Gaussian Mixture Approach to One-To-One Feature Matching", "concept": [ "EM algorithm" ], "topics": [ "match.gaussmix" ] }, { "page": "match.kmeans", "title": "K-Means Matching Algorithm", "topics": [ "match.kmeans" ] }, { "page": "match.rec", "title": "Recursive Initialization Method", "topics": [ "match.rec" ] }, { "page": "match.template", "title": "Template Matching", "topics": [ "match.template" ] }, { "page": "objective.fun", "title": "Calculate Cost of Multidimensional Assignment", "topics": [ "objective.fun" ] }, { "page": "objective.gen.fun", "title": "Objective Value in One-To-One Feature Matching with Balanced or Unbalanced Data", "topics": [ "objective.gen.fun" ] }, { "page": "optdigits", "title": "Handwritten Digits Data", "topics": [ "optdigits" ] }, { "page": "predict.matchFeat", "title": "Match New Feature Vectors To Existing Clusters", "topics": [ "predict.matchFeat" ] }, { "page": "print.matchFeat", "title": "Print a matchFeat Object", "topics": [ "print.matchFeat" ] }, { "page": "Rand.index", "title": "Rand Index of Agreement Between Two Partitions", "topics": [ "Rand.index" ] }, { "page": "summary.matchFeat", "title": "Summarize a matchFeat Object", "topics": [ "summary.matchFeat" ] } ], "_rundeps": [ "clue", "cluster", "codetools", "foreach", "iterators" ], "_score": 1, "_indexed": true, "_nocasepkg": "matchfeat", "_universes": [ "ddegras" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "1.0", "date": "2026-05-28T08:25:33.000Z", "distro": "noble", "commit": "9c76900d9a83397c30d5bc607dddd70da8e53529", 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