{"schema_version":1,"metadata":{"branch":"current","release":"7.9","architecture":"amd64","generated_at":"2026-09-09T04:04:41.004595+00:00","source_url":"https://cdn.openbsd.org/pub/OpenBSD/snapshots/packages/amd64/sqlports-7.55.tgz","source_sha256":"fcdbba1b9df747882aa9bab4af20ebec8dac10655069c90f1cd4145c06e1235e","package_count":12031,"source_kind":"sqlports"},"package":{"name":"p5-AI-NeuralNet-Mesh-0.44p3","path":"math/p5-AI-NeuralNet-Mesh","url":"/packages/current/math/p5-AI-NeuralNet-Mesh/","comment":"module to implement an accurate neural network mesh","homepage":"https://metacpan.org/release/AI-NeuralNet-Mesh","maintainer":"The OpenBSD ports mailing-list <ports@openbsd.org>","description":"AI::NeuralNet::Mesh is an optimized, accurate neural network Mesh.\nIt was designed with accuracy and speed in mind. \n\nThis network model is very flexible. It will allow for classic binary\noperation or any range of integer or floating-point inputs you care\nto provide. With this you can change activation types on a per node or\nper layer basis (you can even include your own anonymous subs as \nactivation types). You can add sigmoid transfer functions and control\nthe threshold. You can learn data sets in batch, and load CSV data\nset files. You can do almost anything you need to with this module.\n","package_architecture":"*","stem":"p5-AI-NeuralNet-Mesh","readme":null,"dependencies":[{"path":"archivers/unzip","type":"build","package_spec":"","url":"/packages/current/archivers/unzip/"}],"reverse_dependencies":{"count":0,"url":null},"categories":["math","perl5"],"flavors":[],"only_for_architectures":[],"not_for_architectures":[]}}