{"id":19267055,"url":"https://github.com/mljs/kernel","last_synced_at":"2025-08-31T22:35:48.035Z","repository":{"id":57298978,"uuid":"46419956","full_name":"mljs/kernel","owner":"mljs","description":"A factory for kernel functions","archived":false,"fork":false,"pushed_at":"2019-06-29T12:28:34.000Z","size":61,"stargazers_count":1,"open_issues_count":0,"forks_count":2,"subscribers_count":5,"default_branch":"master","last_synced_at":"2024-10-04T19:06:09.138Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"JavaScript","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":"History.md","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":"2015-11-18T13:19:33.000Z","updated_at":"2019-06-29T12:28:36.000Z","dependencies_parsed_at":"2022-08-26T18:02:28.909Z","dependency_job_id":null,"html_url":"https://github.com/mljs/kernel","commit_stats":null,"previous_names":[],"tags_count":11,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mljs%2Fkernel","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mljs%2Fkernel/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mljs%2Fkernel/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mljs%2Fkernel/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mljs","download_url":"https://codeload.github.com/mljs/kernel/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":223876400,"owners_count":17218387,"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":"2024-11-09T20:09:51.221Z","updated_at":"2025-04-21T19:32:38.131Z","avatar_url":"https://github.com/mljs.png","language":"JavaScript","funding_links":[],"categories":[],"sub_categories":[],"readme":"# ml-kernel\n\n[![NPM version][npm-image]][npm-url]\n[![build status][travis-image]][travis-url]\n[![npm download][download-image]][download-url]\n\nA factory for kernel functions.\n\n## Installation\n\n`$ npm i ml-kernel`\n\n## Usage\n\n### new Kernel(type, options)\n\nThis function can be called with a matrix of input vectors.\nand optional landmarks. If no landmark is provided, the input vectors will be used.\n\n**Available kernels**:\n\n- `linear` - Linear kernel\n- `gaussian` or `rbf` - [Gaussian (radial basis function) kernel](https://github.com/mljs/kernel-gaussian)\n- `polynomial` or `poly` - [Polynomial kernel](https://github.com/mljs/kernel-polynomial)\n- `exponential` - [Exponential kernel](http://crsouza.com/2010/03/kernel-functions-for-machine-learning-applications/#exponential)\n- `laplacian` - [Laplacian kernel](http://crsouza.com/2010/03/kernel-functions-for-machine-learning-applications/#laplacian)\n- `anova` - [ANOVA kernel](http://crsouza.com/2010/03/kernel-functions-for-machine-learning-applications/#anova)\n- `rational` - [Rational Quadratic kernel](http://crsouza.com/2010/03/kernel-functions-for-machine-learning-applications/#rational)\n- `multiquadratic` - [Multiquadratic kernel](http://crsouza.com/2010/03/kernel-functions-for-machine-learning-applications/#multiquadric)\n- `cauchy` - [Cauchy kernel](http://crsouza.com/2010/03/kernel-functions-for-machine-learning-applications/#cauchy)\n- `histogram` or `min` - [Histogram Intersection kernel](http://crsouza.com/2010/03/kernel-functions-for-machine-learning-applications/#histogram)\n- `sigmoid` or `mlp' - [Sigmoid (hyperbolic tangent) kernel](https://github.com/mljs/kernel-sigmoid)\n\n### kernel.compute(inputs, landmarks)\n\nThis function can be called with a matrix of input vectors and optional landmarks.\nIf no landmark is provided, the input vectors will be used.  \nThe function returns a kernel matrix of feature space vectors.\n\n## License\n\n[MIT](./LICENSE)\n\n[npm-image]: https://img.shields.io/npm/v/ml-kernel.svg?style=flat-square\n[npm-url]: https://npmjs.org/package/ml-kernel\n[travis-image]: https://img.shields.io/travis/mljs/kernel/master.svg?style=flat-square\n[travis-url]: https://travis-ci.org/mljs/kernel\n[download-image]: https://img.shields.io/npm/dm/ml-kernel.svg?style=flat-square\n[download-url]: https://npmjs.org/package/ml-kernel\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmljs%2Fkernel","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmljs%2Fkernel","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmljs%2Fkernel/lists"}