{"id":19267089,"url":"https://github.com/mljs/ml-pipe","last_synced_at":"2025-07-05T23:03:38.187Z","repository":{"id":38258010,"uuid":"467505498","full_name":"mljs/ml-pipe","owner":"mljs","description":null,"archived":false,"fork":false,"pushed_at":"2023-02-13T14:25:17.000Z","size":174,"stargazers_count":2,"open_issues_count":11,"forks_count":0,"subscribers_count":3,"default_branch":"main","last_synced_at":"2025-06-20T14:55:43.026Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"https://mljs.github.io/ml-pipe/","language":"TypeScript","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/mljs.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-03-08T12:36:58.000Z","updated_at":"2023-06-06T19:29:53.000Z","dependencies_parsed_at":"2024-11-09T20:10:23.468Z","dependency_job_id":"7f5a4bc9-1c5d-4c07-8792-e386125375da","html_url":"https://github.com/mljs/ml-pipe","commit_stats":null,"previous_names":["kjappelbaum/ml-pipe"],"tags_count":3,"template":false,"template_full_name":null,"purl":"pkg:github/mljs/ml-pipe","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mljs%2Fml-pipe","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mljs%2Fml-pipe/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mljs%2Fml-pipe/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mljs%2Fml-pipe/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mljs","download_url":"https://codeload.github.com/mljs/ml-pipe/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mljs%2Fml-pipe/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":262210045,"owners_count":23275487,"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":"2024-11-09T20:10:20.348Z","updated_at":"2025-07-05T23:03:38.170Z","avatar_url":"https://github.com/mljs.png","language":"TypeScript","funding_links":[],"categories":[],"sub_categories":[],"readme":"# ml-pipe\n\n[![NPM version][npm-image]][npm-url]\n[![build status][ci-image]][ci-url]\n[![Test coverage][codecov-image]][codecov-url]\n[![npm download][download-image]][download-url]\n\nOrchestrate ML pipelines. One design different to `sklearn` pipelines is that our transformers can have the attribute `onTarget` for use in Pipelines. There, it can be convenient and to simply add a target transformation as a step into the Pipeline\n\n## Installation\n\n`$ npm i ml-pipe`\n\n## Usage\n\n```js\nimport { trainTestSplit } from 'ml-pipe/modelSelection/trainTestSplit';\nimport {Pipeline} from 'ml-pipe/pipeline';\nimport {FCNN} from 'ml-pipe/estimators/neuralNetwork/fcnn'\nimport {StandardScaler, TargetStandardScaler} from 'ml-pipe/transformers/preprocessing/standardScaler'\nimport {meanSquaredError} from 'ml-pipe/metrics/regression'\nconst {xTrain, xTest, yTrain, yTest} = trainTestSplit(x, y, \n    {trainFraction: 0.8,  stratify: yBinned})\n\nconst pipe = new Pipeline([\n    {\n        'name': 'xScale',\n        'object': new StandardScaler()\n    },\n    {\n        'name': 'yScale',\n        'object': new TargetStandardScaler()\n    },\n    {\n        'name': 'model',\n        'object': new FCNN({inputSize: 5})\n    }\n])\n\nawait pipe.fit(XTrain, yTrain)\nconst predictionsTest = pipe.predict(xTest)\nconst mse = meanSquaredError(predictionsTest, yTest)\n```\n\n \n## Related package:\n- [scikit.js](https://github.com/javascriptdata/scikit.js)\n\n\n\n## License\n\n[MIT](./LICENSE)\n\n[npm-image]: https://img.shields.io/npm/v/ml-pipe.svg\n[npm-url]: https://www.npmjs.com/package/ml-pipe\n[ci-image]: https://github.com/kjappelbaum/ml-pipe/workflows/Node.js%20CI/badge.svg?branch=main\n[ci-url]: https://github.com/kjappelbaum/ml-pipe/actions?query=workflow%3A%22Node.js+CI%22\n[codecov-image]: https://img.shields.io/codecov/c/github/kjappelbaum/ml-pipe.svg\n[codecov-url]: https://codecov.io/gh/kjappelbaum/ml-pipe\n[download-image]: https://img.shields.io/npm/dm/ml-pipe.svg\n[download-url]: https://www.npmjs.com/package/ml-pipe\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmljs%2Fml-pipe","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmljs%2Fml-pipe","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmljs%2Fml-pipe/lists"}