{"id":21280633,"url":"https://github.com/borgwardtlab/multi-scones","last_synced_at":"2025-07-13T07:37:05.585Z","repository":{"id":69455284,"uuid":"71109504","full_name":"BorgwardtLab/Multi-SConES","owner":"BorgwardtLab","description":"Multi-task feature selection coupled with multiple network regularizers","archived":false,"fork":false,"pushed_at":"2018-03-05T07:20:27.000Z","size":12,"stargazers_count":3,"open_issues_count":0,"forks_count":4,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-04-06T02:34:57.368Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/BorgwardtLab.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2016-10-17T07:04:52.000Z","updated_at":"2021-01-24T00:20:07.000Z","dependencies_parsed_at":null,"dependency_job_id":"df509280-b0c1-4efc-b3cd-3f09d79b97ca","html_url":"https://github.com/BorgwardtLab/Multi-SConES","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/BorgwardtLab/Multi-SConES","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BorgwardtLab%2FMulti-SConES","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BorgwardtLab%2FMulti-SConES/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BorgwardtLab%2FMulti-SConES/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BorgwardtLab%2FMulti-SConES/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/BorgwardtLab","download_url":"https://codeload.github.com/BorgwardtLab/Multi-SConES/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BorgwardtLab%2FMulti-SConES/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":264785907,"owners_count":23663854,"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":"2024-11-21T10:37:49.499Z","updated_at":"2025-07-13T07:37:05.576Z","avatar_url":"https://github.com/BorgwardtLab.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Multi-SConES\nA multi-task version of SConES, which achieves multi-task feature selection coupled with multiple network regularizers using a maximum-flow algorithm.\n\nPlease see the following paper for detailed information:\n* M. Sugiyama, C.-A. Azencott, D. Grimm, Y. Kawahara, K. M. Borgwardt:\n**Multi-Task Feature Selection on Multiple Networks via Maximum Flows**,\n*Proceedings of the SIAM International Conference on Data Mining (SDM 2014)*, 199-207, 2014\n[[PDF]](http://epubs.siam.org/doi/pdf/10.1137/1.9781611973440.23)\n\n## Usage\nTo load files, type in R (without the `\u003e`, which signifies the prompt):\n```\n\u003e source(\"make.R\")\n\u003e make()\n```\n\nTo run Multi-SConES, type in R:\n```\n\u003e mscones(g = g, X = X, Y = Y, lambda = lambda, eta = eta, mu = mu)\n```\n\n* Two R packages `igraph` and `glmnet` need to be installed\n* `g` is a graph (in igraph format)  \n* `X` is a data matrix (rows: objects, columns: features, each feature corresponds to each vertex in `g`)\n* `Y` is a matrix of response vectors (rows: objects, columns: tasks)  \n* `lambda`, `eta`, `mu` are parameters (they should be determined by grid-search with cross-validation)  \n* output: selected features for each task  \n\n## Example\n```\n\u003e source(\"make.R\")\n\u003e make()\n\u003e d1 \u003c- generate.data(200, 1, seed = 1)\n\u003e d2 \u003c- generate.data(200, 2, seed = 1)\n\u003e X \u003c- d1$x; Y \u003c- cbind(d1$y, d2$y)\n# simulate two tasks d1$y and d2$y, and d1$x and d2$x are the same\n# features from 1 to 44 are causal\n\u003e g \u003c- generate.graph()\n\u003e res \u003c- mscones(g = g, X = X, Y = Y)\n\u003e res\n$`selected features for task 1`\n+ 44/4402 vertices, from 53a17ed:\n [1]  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25\n[26] 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44\n\n$`selected features for task 2`\n+ 44/4402 vertices, from 53a17ed:\n [1]  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25\n[26] 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44\n```\n\n\n## Contact\n\n* Author: [Mahito Sugiyama](http://mahito.info/index_e.html)   \n* Affiliation: ISIR, Osaka University  \n* E-Mail:  mahito@ar.sanken.osaka-u.ac.jp  \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fborgwardtlab%2Fmulti-scones","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fborgwardtlab%2Fmulti-scones","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fborgwardtlab%2Fmulti-scones/lists"}