{"id":19637030,"url":"https://github.com/caiocarneloz/pycc","last_synced_at":"2025-10-24T01:43:06.640Z","repository":{"id":57465454,"uuid":"188087955","full_name":"caiocarneloz/pycc","owner":"caiocarneloz","description":"Python code for the semi-supervised learning method particle competition and cooperation","archived":false,"fork":false,"pushed_at":"2020-04-11T05:05:37.000Z","size":34,"stargazers_count":6,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-04-19T15:32:46.583Z","etag":null,"topics":["complex-networks","graph-based-model","machine-learning","machine-learning-algorithms","python","semi-supervised"],"latest_commit_sha":null,"homepage":"","language":"Python","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/caiocarneloz.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}},"created_at":"2019-05-22T17:52:46.000Z","updated_at":"2025-01-09T13:44:52.000Z","dependencies_parsed_at":"2022-09-13T13:40:30.396Z","dependency_job_id":null,"html_url":"https://github.com/caiocarneloz/pycc","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/caiocarneloz%2Fpycc","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/caiocarneloz%2Fpycc/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/caiocarneloz%2Fpycc/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/caiocarneloz%2Fpycc/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/caiocarneloz","download_url":"https://codeload.github.com/caiocarneloz/pycc/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251284880,"owners_count":21564688,"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":["complex-networks","graph-based-model","machine-learning","machine-learning-algorithms","python","semi-supervised"],"created_at":"2024-11-11T12:32:55.499Z","updated_at":"2025-10-24T01:43:06.546Z","avatar_url":"https://github.com/caiocarneloz.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Particle Competition and Cooperation\nPython code for the semi-supervised learning method \"particle competition and cooperation\". This particular code was used in my master's thesis \"[Aid in Alzheimer's disease diagnosis from magnetic resonance imaging using particle competition and cooperation](https://repositorio.unesp.br/handle/11449/191774)\".\n\n## Getting Started\n#### Installation\nYou need Python 3.7 or later to use **pycc**. You can find it at [python.org](https://www.python.org/).\n\nThe package is avaliable at [PyPI](https://pypi.org). If you have pip, just run:\n```\npip install pypcc\n```\n\nor clone this repo to your local machine using:\n```\ngit clone https://github.com/caiocarneloz/pycc.git\n```\n\n## Usage\nThe usage of this class is pretty similar to [semi-supervised algorithms at scikit-learn](https://scikit-learn.org/stable/modules/label_propagation.html). A \"demo\" code was added to this repository.\n\n## Parameters\nAs arguments, **pycc** receives the values explained below:\n\n---\n- **n_neighbors:** value that represents the number of neighbours in the graph build.\n- **pgrd:** value from 0 to 1 that defines the probability of particles to take the greedy movement.\n- **delta_v:** value from 0 to 1 to control changing rate of the domination levels.\n- **max_iter:** number of epochs until the label propagation stops.\n---\n\n## Citation\nIf you use this algorithm, please cite the original publication:\n\n`Breve, Fabricio Aparecido; Zhao, Liang; Quiles, Marcos Gonçalves; Pedrycz, Witold; Liu, Jiming, \"Particle Competition and Cooperation in Networks for Semi-Supervised Learning,\" Knowledge and Data Engineering, IEEE Transactions on , vol.24, no.9, pp.1686,1698, Sept. 2012`\n\nhttps://doi.org/10.1109/TKDE.2011.119\n\nAccepted Manuscript: https://www.fabriciobreve.com/artigos/ieee-tkde-2009.pdf\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcaiocarneloz%2Fpycc","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcaiocarneloz%2Fpycc","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcaiocarneloz%2Fpycc/lists"}