{ "_id": "6a1e8b541d7bb097a0a69023", "Package": "MaxWiK", "Title": "Machine Learning Method Based on Isolation Kernel Mean Embedding", "Version": "1.0.6", "Authors@R": "person('Yuri', 'Nagornov', email='nagornov.yuri@gmail.com', role = c('aut', 'cre', 'cph'), comment = c(ORCID = '0000-0002-7935-6776') )", "Description": "Incorporates Approximate Bayesian Computation to get a\nposterior distribution and to select a model optimal parameter\nfor an observation point. Additionally, the meta-sampling\nheuristic algorithm is realized for parameter estimation, which\nrequires no model runs and is dimension-independent. A sampling\nscheme is also presented that allows model runs and uses the\nmeta-sampling for point generation. A predictor is realized as\nthe meta-sampling for the model output. All the algorithms\nleverage a machine learning method utilizing the maxima\nweighted Isolation Kernel approach, or 'MaxWiK'. The method\ninvolves transforming raw data to a Hilbert space (mapping) and\nmeasuring the similarity between simulated points and the\nmaxima weighted Isolation Kernel mapping corresponding to the\nobservation point. Comprehensive details of the methodology can\nbe found in the papers Iurii Nagornov (2024)\n and Iurii Nagornov (2023)\n.", "License": "GPL (>= 3)", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.2", "VignetteBuilder": "knitr", "LazyData": "true", "Repository": "https://tughall.r-universe.dev", "Date/Publication": "2025-07-07 05:11:52 UTC", "RemoteUrl": "https://github.com/tughall/maxwik", "RemoteRef": "HEAD", "RemoteSha": "b54ffce4ca7a3e4f71592fcdf7e6b80d488b7cf7", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-02 07:46:51 UTC", "User": "root" }, "Author": "Yuri Nagornov [aut, cre, cph] (ORCID:\n)", "Maintainer": "Yuri Nagornov ", "MD5sum": "bf73222446360f6d1ce0f85153c39b77", "_user": "tughall", "_type": "src", "_file": "MaxWiK_1.0.6.tar.gz", "_fileid": "48408ed1ee7c526c1050c9c3db89112272714e7f03a5ef4ad4e05bc7c872cd6c", "_filesize": 921575, "_sha256": "48408ed1ee7c526c1050c9c3db89112272714e7f03a5ef4ad4e05bc7c872cd6c", "_created": "2026-06-02T07:46:51.000Z", "_published": "2026-06-02T07:50:44.148Z", "_distro": "noble", "_jobs": [ { "job": 79023606950, "time": 152, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7351912179" }, { "job": 79023606939, "time": 149, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7351910930" }, { "job": 79023606922, "time": 141, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "7351902630" }, { "job": 79023606904, "time": 185, "config": "macos-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "7351915976" }, { "job": 79023065744, "time": 205, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7351859870" }, { "job": 79023607015, "time": 110, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7351897879" }, { "job": 79023606964, "time": 90, "config": "windows-devel", "r": "4.7.0", "check": "OK", "artifact": "7351893616" }, { "job": 79023606953, "time": 105, "config": "windows-oldrel", "r": "4.5.3", "check": "OK", "artifact": "7351896394" }, { "job": 79023606934, "time": 109, "config": "windows-release", "r": "4.6.0", "check": "OK", "artifact": "7351897892" } ], "_buildurl": "https://github.com/r-universe/tughall/actions/runs/26805841658", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/tughall/maxwik", "_commit": { "id": "b54ffce4ca7a3e4f71592fcdf7e6b80d488b7cf7", "author": "tugHall ", "committer": "tugHall ", "message": "update CRAN submission\n", "time": 1751865112 }, "_maintainer": { "name": "Yuri Nagornov", "email": "nagornov.yuri@gmail.com", "login": "tughall", "description": "This is software developed by Department of Bioinformatics. \nAuthors: Iurii Nagornov, Mamoru Kato. 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