{"schema_version":1,"metadata":{"branch":"release","release":"7.9","architecture":"amd64","generated_at":"2026-09-09T04:04:02.361425+00:00","source_url":"https://cdn.openbsd.org/pub/OpenBSD/7.9/packages/amd64/sqlports-7.54.tgz","source_sha256":"2de00144847bf9da3a365be982f101dbb55d591ed7a915ea94984a16ab0e0404","package_count":12059,"source_kind":"sqlports"},"package":{"name":"p5-Statistics-Contingency-0.09p0","path":"math/p5-Statistics-Contingency","url":"/packages/release/math/p5-Statistics-Contingency/","comment":"calculate precision, recall, F1, accuracy, etc","homepage":"https://metacpan.org/release/Statistics-Contingency","maintainer":"The OpenBSD ports mailing-list <ports@openbsd.org>","description":"The Statistics::Contingency class helps you calculate several useful\nstatistical measures based on 2x2 \"contingency tables\". These can be\nused for measures to help judge the results of automatic text\ncategorization experiments, but they are useful in other situations\nas well.\n\nThe general usage flow is to tally a whole bunch of results in the\nStatistics::Contingency object, then query that object to obtain the\nmeasures you are interested in. When all results have been collected,\nyou can get a report on accuracy, precision, recall, F1, and so on, with\nboth macro-averaging and micro-averaging over categories.\n","package_architecture":"*","stem":"p5-Statistics-Contingency","readme":null,"dependencies":[{"path":"devel/p5-Params-Validate","type":"runtime","package_spec":"STEM->=0.23","url":"/packages/release/devel/p5-Params-Validate/"},{"path":"devel/p5-Module-Build","type":"build","package_spec":"","url":"/packages/release/devel/p5-Module-Build/"},{"path":"devel/p5-Params-Validate","type":"test","package_spec":"STEM->=0.23","url":"/packages/release/devel/p5-Params-Validate/"}],"reverse_dependencies":{"count":0,"url":null},"categories":["math","perl5"],"flavors":[],"only_for_architectures":[],"not_for_architectures":[]}}