{
 "culture": "en-US",
 "name": "DensityBasedClustering",
 "guid": "",
 "catalogPath": "",
 "snippet": "Finds clusters of point features within surrounding noise based on their spatial distribution. Time can also be incorporated to find space-time clusters.",
 "description": "Finds clusters of point features within surrounding noise based on their spatial distribution. Time can also be incorporated to find space-time clusters.",
 "summary": "Finds clusters of point features within surrounding noise based on their spatial distribution. Time can also be incorporated to find space-time clusters.",
 "title": "DensityBasedClustering",
 "tags": [
  "aggregate",
  "classify",
  "cluster",
  "clustering",
  "compact",
  "data space",
  "dbscan",
  "divide",
  "group",
  "grouping",
  "grouping analysis",
  "hdbscan",
  "like",
  "machine learning",
  "optics",
  "partition",
  "pattern",
  "point pattern",
  "unsupervised machine learning"
 ],
 "type": "Geoprocessing Service",
 "typeKeywords": [
  "Tool",
  "Service",
  "Geoprocessing Service",
  "Web Tool",
  "ArcGIS Server"
 ],
 "thumbnail": "",
 "url": "https://gisdev.wsscwater.com/server",
 "minScale": 0,
 "maxScale": 0,
 "spatialReference": "",
 "accessInformation": "",
 "licenseInfo": ""
}