{"id":15767212,"url":"https://github.com/lmangani/voip-classifier","last_synced_at":"2025-03-31T11:09:59.566Z","repository":{"id":145716719,"uuid":"109906264","full_name":"lmangani/voip-classifier","owner":"lmangani","description":"Simple kNN classifier for VoIP and RTC Metrics","archived":false,"fork":false,"pushed_at":"2017-11-08T12:01:28.000Z","size":10,"stargazers_count":3,"open_issues_count":0,"forks_count":0,"subscribers_count":4,"default_branch":"master","last_synced_at":"2024-10-04T13:21:46.385Z","etag":null,"topics":["jitter","k-nearest-neighbours","knn","machine-learning","mean-opinion-score","ml","mos","packet-loss","rtc","rtt","voip"],"latest_commit_sha":null,"homepage":"http://qxip.net","language":"JavaScript","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/lmangani.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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":"2017-11-08T00:14:13.000Z","updated_at":"2022-06-30T11:15:55.000Z","dependencies_parsed_at":"2023-08-26T08:34:22.882Z","dependency_job_id":null,"html_url":"https://github.com/lmangani/voip-classifier","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lmangani%2Fvoip-classifier","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lmangani%2Fvoip-classifier/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lmangani%2Fvoip-classifier/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lmangani%2Fvoip-classifier/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/lmangani","download_url":"https://codeload.github.com/lmangani/voip-classifier/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246458000,"owners_count":20780677,"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":["jitter","k-nearest-neighbours","knn","machine-learning","mean-opinion-score","ml","mos","packet-loss","rtc","rtt","voip"],"created_at":"2024-10-04T13:21:09.909Z","updated_at":"2025-03-31T11:09:59.545Z","avatar_url":"https://github.com/lmangani.png","language":"JavaScript","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cimg src=\"https://user-images.githubusercontent.com/1423657/32525847-b63539c0-c426-11e7-93d2-3aba164d12a6.png\" width=150\u003e\n\n# VoIP-classifier\n\nSimple kNN classifier for VoIP and RTC Metrics\n\n**kNN** stands for *k-Nearest-Neighbours*, which is a Supervised machine learning algorithm used for classification, determining the class of a data point based on the maximum number of neighbors the data point has belonging to the same class.\n\n-------------\n\n## MOS Classifier\n\n**MOS** stands for Mean Opinion Score, a commonly used measure for audio and video VoIP quality evaluation. This example only accounts for network performance related parameters negatively affecting the score.\n\n#### Dataset Warning\nIn this example, a fictional Data set is provided for trainig ml.js KNN module using various combinations of Packet Loss, Jitter and Round-Trip-Tip measurements and their resulting MOS rank in class 1-4. This dataset is oversimplified, purely illustrative for educational purposes and does _not_ necessarily represent actual conditions.\n\n\n## Examples\n#### Optimal Values\n```\nprompt: Lost%/10:  0.0 (0%0\nprompt: Jitter/100:  0.5 (50ms)\nprompt: RTT/100:  1.0 (100ms)\nprompt: CodecType:  0 (PCMU)\nWith 0,0.5,1,0 -- type =  MOS4\n```\n\n#### High Packet Loss (50%)\n```\nprompt: Lost%/10:  0.5 (50%)\nprompt: Jitter/100:  1.0 (100ms)\nprompt: RTT/100:  1.0 (100ms)\nprompt: CodecType:  0 (PCMU)\nWith 0.5,1,1,0 -- type =  MOS1\n```\n-----------------\n\n### Credits\nThis mere adaption is heavily based on the awesome [Machine Learning with JavaScript](https://hackernoon.com/machine-learning-with-javascript-part-2-da994c17d483) tutorial by [Abhishek Soni](https://github.com/abhisheksoni27)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flmangani%2Fvoip-classifier","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flmangani%2Fvoip-classifier","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flmangani%2Fvoip-classifier/lists"}