{"id":22848397,"url":"https://github.com/feedzai/fos-r","last_synced_at":"2025-05-07T04:22:32.309Z","repository":{"id":13389009,"uuid":"16077151","full_name":"feedzai/fos-r","owner":"feedzai","description":"Feedzai Open Scoring Server R Module","archived":false,"fork":false,"pushed_at":"2016-03-01T16:06:31.000Z","size":97,"stargazers_count":2,"open_issues_count":0,"forks_count":3,"subscribers_count":31,"default_branch":"master","last_synced_at":"2025-03-31T06:11:35.372Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Java","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/feedzai.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2014-01-20T17:06:37.000Z","updated_at":"2016-01-19T18:00:17.000Z","dependencies_parsed_at":"2022-09-26T19:11:12.633Z","dependency_job_id":null,"html_url":"https://github.com/feedzai/fos-r","commit_stats":null,"previous_names":[],"tags_count":9,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/feedzai%2Ffos-r","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/feedzai%2Ffos-r/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/feedzai%2Ffos-r/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/feedzai%2Ffos-r/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/feedzai","download_url":"https://codeload.github.com/feedzai/fos-r/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252811185,"owners_count":21807904,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-12-13T04:11:36.680Z","updated_at":"2025-05-07T04:22:32.283Z","avatar_url":"https://github.com/feedzai.png","language":"Java","funding_links":[],"categories":[],"sub_categories":[],"readme":"# feedzai Open Scoring Server (FOS) - R m Scoring and Training module\n\nfos-r is a [fos-core] [R] implementation\n\n[![Build Status](https://feedzaios.ci.cloudbees.com/buildStatus/icon?job=fos-r)](https://feedzaios.ci.cloudbees.com/job/fos-r/)\n\n[![CloudbeesDevCloud](http://www.cloudbees.com/sites/default/files/Button-Built-on-CB-1.png)](http://www.cloudbees.com/dev)\n\n## Why FOS\n\nThere are pretty good machine learning training and scoring frameworks/libraries out there, but they don't provide the\nfollowing benefits:\n\n1. Common API: fos provides a common abstraction for model attributes, model training and model scoring. Using a [Weka]\nbased classifier will use have exactly the same API as using a R based classifier.\n1. Scoring \u0026 Training as a remote service: Training and scoring can be farmed to dedicated servers in the network\nenabling both vertical and horizontal scaling.\n1. Import and Export models: A model could be trained in a development box and imported seamlessly into a remote server\n1. Scalable and low latency scoring: Marshalling and Unmarshalling scoring requests/responses can be responsible\nfor a significant amount of overhead. Along with the slow RMI based interface, fos also supports scoring using [Kryo].\n\n## Compiling fos-r\n\nYou need:\n\n1. [Java SDK]: Java 7\n1. [Maven]: Tested with maven 3.0.X\n1. [fos-core]\n1. [R]: Tested against R 2.15 on Linux (Tested on debian, centos, ubuntu)\n1. Access to maven central repo (or a local proxy)\n\n\nAfter installing [R] you need to install R RServe library\n\nTo install Rserve open a command line, start R and type the following command:\n\n ```R\n install.packages(\"Rserve\")\n ```\n\nfos-r provides a built-in training module using [randomForest]. In order to use it\nyou need to install the following R packages:\n\n```R\ninstall.packages(\"randomForest\")\ninstall.packages(\"doMC\")\ninstall.packages(\"foreach\")\ninstall.packages(\"foreign\")\ninstall.packages(\"e1071\")\ninstall.packages(\"kernlab\")\ninstall.packages(\"XML\")\ninstall.packages(\"pmml\")\n```\n\nAfter Rserve has been installed successfully, start a rserve daemon:\n\n```Shell\nR --no-save --slave -e \"library(Rserve);Rserve(args='--no-save --slave');\"\n```\n\nAfter [Java SDK] and [Maven] have been installed run the following command\n\n```Shell\nmvn clean install\n```\n\nThis should compile fos-r, ran all the tests and install all modules into your local maven repo.\n\n## Running FOS-R \n\nThe default FOS-R package uses [fos-weka]. You need to set `fos.factoryName` in fos.properties like this:\n\n```\nfos.factoryName=com.feedzai.fos.impl.r.RManagerFactory\n```\n\n[Kryo]: https://github.com/EsotericSoftware/kryo\n[fos-r]: https://github.com/feedzai/fos-r\n[fos-core]: https://github.com/feedzai/fos-core\n[fos-weka]: https://github.com/feedzai/fos-weka\n[Weka]: http://www.cs.waikato.ac.nz/ml/weka/\n[R]: http://www.r-project.org/\n[Maven]: http://maven.apache.org/\n[Java SDK]: http://www.oracle.com/technetwork/java/javase/downloads/jdk7-downloads-1880260.html\n[randomForest]: http://cran.r-project.org/web/packages/randomForest/index.html\n\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffeedzai%2Ffos-r","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffeedzai%2Ffos-r","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffeedzai%2Ffos-r/lists"}