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Generated by documentation.js. Update this documentation by updating the source code. -->\n\n## Dbscan\n\nPoint classification within the cluster.\n\nType: (`\"core\"` | `\"edge\"` | `\"noise\"`)\n\n## DbscanProps\n\n**Extends GeoJsonProperties**\n\nProperties assigned to each clustered point.\n\nType: [object][1]\n\n### Properties\n\n*   `dbscan` **[Dbscan][2]?** type of point it has been classified as\n*   `cluster` **[number][3]?** associated clusterId\n\n## clustersDbscan\n\nTakes a set of [points][4] and partition them into clusters according to [DBSCAN's][5] data clustering algorithm.\n\n### Parameters\n\n*   `points` **[FeatureCollection][6]<[Point][4]>** to be clustered\n*   `maxDistance` **[number][3]** Maximum Distance between any point of the cluster to generate the clusters (kilometers by default, see options)\n*   `options` **[Object][1]** Optional parameters (optional, default `{}`)\n\n    *   `options.units` **Units** in which `maxDistance` is expressed, Supports all valid Turf [Units][7] (optional, default `\"kilometers\"`)\n    *   `options.mutate` **[boolean][8]** Allows GeoJSON input to be mutated (optional, default `false`)\n    *   `options.minPoints` **[number][3]** Minimum number of points to generate a single cluster,\n        points which do not meet this requirement will be classified as an 'edge' or 'noise'. (optional, default `3`)\n\n### Examples\n\n```javascript\n// create random points with random z-values in their properties\nvar points = turf.randomPoint(100, {bbox: [0, 30, 20, 50]});\nvar maxDistance = 100;\nvar clustered = turf.clustersDbscan(points, maxDistance);\n\n//addToMap\nvar addToMap = [clustered];\n```\n\nReturns **[FeatureCollection][6]<[Point][4], [DbscanProps][9]>** Clustered Points with an additional two properties associated to each Feature:*   {number} cluster - the associated clusterId\n*   {string} dbscan - type of point it has been classified as ('core'|'edge'|'noise')\n\n[1]: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Object\n\n[2]: #dbscan\n\n[3]: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number\n\n[4]: https://tools.ietf.org/html/rfc7946#section-3.1.2\n\n[5]: https://en.wikipedia.org/wiki/DBSCAN\n\n[6]: https://tools.ietf.org/html/rfc7946#section-3.3\n\n[7]: https://turfjs.org/docs/api/types/Units\n\n[8]: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Boolean\n\n[9]: #dbscanprops\n\n<!-- This file is automatically generated. Please don't edit it directly. If you find an error, edit the source file of the module in question (likely index.js or index.ts), and re-run \"yarn docs\" from the root of the turf project. -->\n\n---\n\nThis module is part of the [Turfjs project](https://turfjs.org/), an open source module collection dedicated to geographic algorithms. It is maintained in the [Turfjs/turf](https://github.com/Turfjs/turf) repository, where you can create PRs and issues.\n\n### Installation\n\nInstall this single module individually:\n\n```sh\n$ npm install @turf/clusters-dbscan\n```\n\nOr install the all-encompassing @turf/turf module that includes all modules as functions:\n\n```sh\n$ npm install @turf/turf\n```\n","readmeFilename":"README.md","users":{"charlietango592":true}}