{"id":19817228,"url":"https://github.com/rmodi6/perceptron","last_synced_at":"2025-02-28T15:03:39.234Z","repository":{"id":147566537,"uuid":"245017646","full_name":"rmodi6/perceptron","owner":"rmodi6","description":"Perceptron learning algorithm implemented in Python","archived":false,"fork":false,"pushed_at":"2020-03-24T01:56:47.000Z","size":34,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-01-11T08:08:58.008Z","etag":null,"topics":["cross-validation","empirical-risk-minimization","machine-learning","perceptron-learning-algorithm","python38"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/rmodi6.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":"2020-03-04T22:31:10.000Z","updated_at":"2020-03-24T02:49:42.000Z","dependencies_parsed_at":"2023-04-14T04:08:13.026Z","dependency_job_id":null,"html_url":"https://github.com/rmodi6/perceptron","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/rmodi6%2Fperceptron","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rmodi6%2Fperceptron/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rmodi6%2Fperceptron/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rmodi6%2Fperceptron/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/rmodi6","download_url":"https://codeload.github.com/rmodi6/perceptron/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241170557,"owners_count":19921651,"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":["cross-validation","empirical-risk-minimization","machine-learning","perceptron-learning-algorithm","python38"],"created_at":"2024-11-12T10:12:04.569Z","updated_at":"2025-02-28T15:03:39.209Z","avatar_url":"https://github.com/rmodi6.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Perceptron\n# Adaptive Boosting\nThe path to dataset can be provided using the `dataset` parameter and `mode` parameter can be used to specify the mode in which to execute perceptron. There are two modes available: `erm` for Empirical Risk Minimization and `cv` for 10 fold Cross Validation. For example:\n```bash\npython perceptron.py --dataset 'path/to/dataset' --mode erm\n```","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frmodi6%2Fperceptron","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frmodi6%2Fperceptron","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frmodi6%2Fperceptron/lists"}