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status](https://img.shields.io/github/actions/workflow/status/mlange-42/bbn/tests.yml?branch=main\u0026label=Tests\u0026logo=github)](https://github.com/mlange-42/bbn/actions/workflows/tests.yml)\n[![Go Report Card](https://goreportcard.com/badge/github.com/mlange-42/bbn)](https://goreportcard.com/report/github.com/mlange-42/bbn)\n[![Go Reference](https://img.shields.io/badge/reference-%23007D9C?logo=go\u0026logoColor=white\u0026labelColor=gray)](https://pkg.go.dev/github.com/mlange-42/bbn)\n[![GitHub](https://img.shields.io/badge/github-repo-blue?logo=github)](https://github.com/mlange-42/bbn)\n\nBayesian Belief Network CLI/TUI tool and [Go](https://go.dev) module.\n\n![screenshot](https://github.com/mlange-42/bbn/assets/44003176/d81e9225-4480-4e37-a8c0-08ccb02cfe73)\n\n## Features\n\n* Visualize, query and explore networks in the interactive TUI app `bbni`.\n* Supports decision networks (aka influence diagrams), including sequential decisions.\n* Provides logic nodes for logic inference in addition to probabilistic inference.\n* Train and query networks from the command line with `bbn`.\n* Human-readable YAML format for networks, as well as BIF-XML.\n* Plenty of [examples](https://github.com/mlange-42/bbn/tree/main/_examples) with introductory text, shown in-app.\n\n## Installation\n\n### Command line tools\n\nPre-compiled binaries for Linux, Windows and MacOS are available in the\n[Releases](https://github.com/mlange-42/bbn/releases).\n\n\u003e Alternatively, install the latest development versions of `bbn` and `bbni` using [Go](https://go.dev):\n\u003e ```shell\n\u003e go install github.com/mlange-42/bbn/cmd/bbn@main\n\u003e go install github.com/mlange-42/bbn/cmd/bbni@main\n\u003e ```\n\n### Library\n\n⚠️ Please be aware that the `bbn` Go module is still under development and highly unstable.\n\nAdd BBN to a Go project:\n\n```\ngo get github.com/mlange-42/bbn\n```\n\n## Usage\n\n### Command line tools\n\nTry the famous sprinkler example:\n\n```\nbbni _examples/bbn/sprinkler.yml\n```\n\nSame example with the command line tool, given some evidence:\n\n```\nbbn inference _examples/bbn/sprinkler.yml -e Rain=no,GrassWet=yes\n```\n\nTrain a network from data:\n\n```\nbbn train _examples/bbn/fruits-untrained.yml _examples/bbn/fruits.csv\n```\n\nAlso try the other examples in folder [_examples](https://github.com/mlange-42/bbn/tree/main/_examples).\nRun them with `bbni` and play around, but also view their `.yml` files\nto get an idea how to create Bayesian Networks.\n\n### Library\n\n⚠️ Please be aware that the `bbn` Go module is still under development and highly unstable.\n\nSee the examples in the [API reference](https://pkg.go.dev/github.com/mlange-42/bbn).\n\n## License\n\nThis project is distributed under the [MIT license](./LICENSE).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmlange-42%2Fbbn","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmlange-42%2Fbbn","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmlange-42%2Fbbn/lists"}