{"id":17003340,"url":"https://github.com/webyneter/components-analysis","last_synced_at":"2026-05-06T12:35:59.081Z","repository":{"id":101934659,"uuid":"45421488","full_name":"webyneter/Components-Analysis","owner":"webyneter","description":"Training application for performing Kernel/Principle Components Analysis","archived":false,"fork":false,"pushed_at":"2016-10-25T17:08:34.000Z","size":381,"stargazers_count":0,"open_issues_count":1,"forks_count":0,"subscribers_count":0,"default_branch":"master","last_synced_at":"2025-03-22T09:44:37.182Z","etag":null,"topics":["components-analysis","kpca-analysis","pca-analysis","principle-component-analysis"],"latest_commit_sha":null,"homepage":"","language":"C#","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/webyneter.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":"2015-11-02T20:55:08.000Z","updated_at":"2018-10-26T20:22:41.000Z","dependencies_parsed_at":null,"dependency_job_id":"c0381e1e-79a7-427d-bab9-b6ed9a58978d","html_url":"https://github.com/webyneter/Components-Analysis","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/webyneter/Components-Analysis","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/webyneter%2FComponents-Analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/webyneter%2FComponents-Analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/webyneter%2FComponents-Analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/webyneter%2FComponents-Analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/webyneter","download_url":"https://codeload.github.com/webyneter/Components-Analysis/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/webyneter%2FComponents-Analysis/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32694346,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-06T08:33:17.875Z","status":"ssl_error","status_checked_at":"2026-05-06T08:33:17.221Z","response_time":117,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 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":["components-analysis","kpca-analysis","pca-analysis","principle-component-analysis"],"created_at":"2024-10-14T04:30:25.862Z","updated_at":"2026-05-06T12:35:59.064Z","avatar_url":"https://github.com/webyneter.png","language":"C#","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Components-Analysis\nTraining application for performing Kernel/Principle Components Analysis.\n\n![General application view]([screenshots]/general.jpg \"General application view\")\n\nGoals:\n- Introduce working project lifecycle support (project creation, saving, opening, etc.)\n- Implement system/user settings UI-based control support.\n- Introduce English/Russian localization.\n\nThe components analysis itself had almost nothing to do with the primary objective I pursued: Improving programming and WinForms UI adjusting skills. Since K/PCA functionality was considered somewhat placeholding, I made extensive use of amazing [Accord.NET Machine Learning Framework](http://accord-framework.net/), [AForge.NET :: Framework](www.aforgenet.com/framework/) frameworks to implement it, so I give their developers much credit.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwebyneter%2Fcomponents-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fwebyneter%2Fcomponents-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwebyneter%2Fcomponents-analysis/lists"}