{"id":18786493,"url":"https://github.com/tetsuok/go-pegasos","last_synced_at":"2025-04-13T13:06:54.945Z","repository":{"id":3397869,"uuid":"4447272","full_name":"tetsuok/go-pegasos","owner":"tetsuok","description":"An implementation of the Pegasos algorithm for solving Support Vector Machines in Go","archived":false,"fork":false,"pushed_at":"2015-01-18T09:14:31.000Z","size":203,"stargazers_count":7,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-04-13T13:06:48.868Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Go","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/tetsuok.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":"2012-05-25T15:59:31.000Z","updated_at":"2021-10-20T01:59:38.000Z","dependencies_parsed_at":"2022-09-10T20:00:18.153Z","dependency_job_id":null,"html_url":"https://github.com/tetsuok/go-pegasos","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tetsuok%2Fgo-pegasos","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tetsuok%2Fgo-pegasos/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tetsuok%2Fgo-pegasos/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tetsuok%2Fgo-pegasos/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/tetsuok","download_url":"https://codeload.github.com/tetsuok/go-pegasos/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248717242,"owners_count":21150389,"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":"2024-11-07T20:51:42.614Z","updated_at":"2025-04-13T13:06:54.921Z","avatar_url":"https://github.com/tetsuok.png","language":"Go","funding_links":[],"categories":[],"sub_categories":[],"readme":"go-pegasos\n==========\n\nAn implementation of the Pegasos algorithm [1] for solving Support Vector Machines in Go.\n\nBuild Instructions\n------------------\n\n### Software Requirements ###\n\n* [Go](http://golang.org/)\n\n### Get the code ###\n\n    $ go get github.com/tetsuok/go-pegasos\n\n### Installation of commands ###\n\n    $ go install github.com/tetsuok/go-pegasos/pegasos_learn\n    $ go install github.com/tetsuok/go-pegasos/pegasos_test\n\n### Testing ###\n\n    $ go test github.com/tetsuok/go-pegasos/pegasos\n\nIf you want to run testing including benchmarks, use `check.sh`\n\n    $ ./check.sh\n\n\nUsage\n-----\n\n### Data format ###\n\ngo-pegasos accepts the same representation of training data as\n[SVMlight](http://svmlight.joachims.org/) uses. This format has\npotential to handle large sparse feature vectors.\n\n### Training ###\n\n    $ ./pegasos_learn -m model_file train_file\n\nPlease note \"-m\" is required to save the trained model.\n\n#### Options #####\n\n* -k INT: number of block size.\n* -lambda FLOAT: Regularization parameter\n* -m STRING: model file\n* -r INT: seed\n* -t INT: number of iterations\n* -test STRING: If you set a test file, you can do training and testing at a time.\n\n### Testing with trained model ###\n\n    $ ./pegasos_test test_file model_file\n\n### Reference ####\n\n[1] Shalev-Shwartz, Shai and Singer, Yoram and Srebro,\nNathan. Pegasos: Primal Estimated sub-GrAdient SOlver for SVM.\nIn Proceedings of the 24th international conference on Machine learning\n(ICML). 2007. pages 807-814.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftetsuok%2Fgo-pegasos","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftetsuok%2Fgo-pegasos","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftetsuok%2Fgo-pegasos/lists"}