{"id":19974353,"url":"https://github.com/gbroques/dbscan","last_synced_at":"2025-05-04T02:32:38.561Z","repository":{"id":32740055,"uuid":"130616435","full_name":"gbroques/dbscan","owner":"gbroques","description":"DBSCAN density-based clustering algorithm in Python.","archived":false,"fork":false,"pushed_at":"2022-12-08T00:59:24.000Z","size":297,"stargazers_count":10,"open_issues_count":4,"forks_count":1,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-04-08T01:51:17.299Z","etag":null,"topics":["clustering-algorithm","dbscan","dbscan-clustering","density-based-clustering","eps","python","python-3"],"latest_commit_sha":null,"homepage":null,"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/gbroques.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":"2018-04-22T23:30:40.000Z","updated_at":"2024-07-28T09:02:29.000Z","dependencies_parsed_at":"2023-01-14T22:05:25.928Z","dependency_job_id":null,"html_url":"https://github.com/gbroques/dbscan","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/gbroques%2Fdbscan","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gbroques%2Fdbscan/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gbroques%2Fdbscan/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gbroques%2Fdbscan/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/gbroques","download_url":"https://codeload.github.com/gbroques/dbscan/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252279070,"owners_count":21722833,"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":["clustering-algorithm","dbscan","dbscan-clustering","density-based-clustering","eps","python","python-3"],"created_at":"2024-11-13T03:14:46.630Z","updated_at":"2025-05-04T02:32:38.223Z","avatar_url":"https://github.com/gbroques.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# DBSCAN\n\n[![Build Status](https://travis-ci.org/gbroques/dbscan.svg?branch=master)](https://travis-ci.org/gbroques/dbscan)\n[![Coverage Status](https://coveralls.io/repos/github/gbroques/dbscan/badge.svg?branch=master)](https://coveralls.io/github/gbroques/dbscan?branch=master)\n\nDensity-Based Spatial Clustering of Applications with Noise (DBSCAN) implementation in Python.\n\nAPI inspired by Scikit-learn.\n\n## Usage\n\n```python\nimport numpy as np\n\nfrom dataviz import generate_clusters\nfrom dataviz import plot_clusters\nfrom dbscan import DBSCAN\n\ndef generate_data(num_clusters: int, seed=None) -\u003e np.ndarray:\n    num_points = 20\n    spread = 7\n    bounds = (1, 100)\n    clusters = generate_clusters(num_clusters, num_points, spread, bounds, bounds, seed)\n    return np.array(clusters)\n\nnum_clusters = 4\nclusters = generate_data(num_clusters, seed=1)\ndbscan = DBSCAN(eps=7, min_samples=5)\ndbscan.fit(clusters)\nplot_clusters(clusters, dbscan.labels_, dbscan.components_)\n```\n\n![dbscan plot](dbscan-plot.png)\n\n* Red crosses denote **core points**\n\n**Reference:**  *Introduction to Data Mining* (1st Edition) by Pang-Ning Tan\nSection 8.4, Page 526\n\n**Original Paper:** Ester, Martin, Hans-Peter Kriegel, Jörg Sander, and Xiaowei Xu. \"A density-based algorithm for discovering clusters in large spatial databases with noise.\" In Kdd, vol. 96, no. 34, pp. 226-231. 1996.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgbroques%2Fdbscan","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgbroques%2Fdbscan","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgbroques%2Fdbscan/lists"}