{"id":32203447,"url":"https://github.com/grasia/knnp","last_synced_at":"2026-02-23T05:02:11.428Z","repository":{"id":56936604,"uuid":"232557960","full_name":"Grasia/knnp","owner":"Grasia","description":"Time Series Forecasting using K-Nearest Neighbors Algorithm (Parallel approach)","archived":false,"fork":false,"pushed_at":"2020-01-17T09:58:38.000Z","size":529,"stargazers_count":1,"open_issues_count":1,"forks_count":0,"subscribers_count":5,"default_branch":"package-release","last_synced_at":"2025-12-09T21:18:51.622Z","etag":null,"topics":["knearest-neighbor-algorithm","parallel","time-series-forecasting"],"latest_commit_sha":null,"homepage":"","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"agpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Grasia.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":"2020-01-08T12:25:43.000Z","updated_at":"2025-09-04T05:29:32.000Z","dependencies_parsed_at":"2022-08-21T06:21:02.479Z","dependency_job_id":null,"html_url":"https://github.com/Grasia/knnp","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/Grasia/knnp","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Grasia%2Fknnp","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Grasia%2Fknnp/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Grasia%2Fknnp/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Grasia%2Fknnp/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Grasia","download_url":"https://codeload.github.com/Grasia/knnp/tar.gz/refs/heads/package-release","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Grasia%2Fknnp/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29738083,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-23T04:51:08.365Z","status":"ssl_error","status_checked_at":"2026-02-23T04:49:15.865Z","response_time":90,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":["knearest-neighbor-algorithm","parallel","time-series-forecasting"],"created_at":"2025-10-22T04:39:39.634Z","updated_at":"2026-02-23T05:02:11.415Z","avatar_url":"https://github.com/Grasia.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"# knnp : Time Series Prediction using K-Nearest Neighbors Algorithm (Parallel)\n\nFirst release was developed as an End-of-Degree Project.\n\nFurther improvements have been made now as a project from GRASIA investigation group: \nhttps://grasia.fdi.ucm.es/\n\nPurpose\n----------\nThis package intends to provide R users or anyone interested in the field of time series prediction the possibility of aplying the k-nearest neighbors algorithm to time series prediction problems. Two main functionalities are provided:\n- Time series prediction using this method.\n- Optimization of parameteres *k* and *d* of the algorithm.\n\nAll the code involved has been optimized to:\n- Parallelize critic components as the process of optimization of parameteres *k* and *d* or the calculation of distances.\n- Use memory efficiently.\n\nAuthors\n----------\n- Daniel Bastarrica Lacalle\n- Javier Berdecio Trigueros\n\nDirectors\n----------\n- Javier Arroyo Gallardo\n- Albert Meco Alias\n\nMaintainer\n----------\n- Daniel Bastarrica Lacalle\n\nLicense\n----------\nAGPL-3\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgrasia%2Fknnp","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgrasia%2Fknnp","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgrasia%2Fknnp/lists"}