sdbscan

Super fast density based spatial clustering DBSCAN implementation for unidimiensional and multidimensional data. Works on nodejs and browser.

Installation

``
npm install sdbscan
`

Usage

$3

`javascript
const sdbscan = require("sdbscan");

var data = [0, 1, 100, 101, 2, 102, 3, 104, 4, 103, 105, 5];
var res = sdbscan(data,2,3);
`

$3


`html









`

Results

`javascript
{
"noise": [],
"clusters": [
{
"id": 0,
"data": [5,4,3,2,1,0]
},
{
"id": 1,
"data": [105,103,104,102,101,100]
}
]
}
``

API

$3

Calculates unidimiensional and multidimensional dbscan clustering on data. Parameters are:
data Unidimiensional or multidimensional array of values to be clustered. for unidimiensional data, takes the form of a simple array [1,2,3.....,n]*. For multidimensional data, takes a
NxM array [[1,2],[2,3]....[n,m]]
* epsilon Maximum distance for two points to be considered in the same region.
min Minimal region size. If a region for a point is lesser than min*, this point will be considered as noise (cannot be included in any group).

The function will return an object with the following data:
* noise Points that cannot be added to any cluster.
* clusters An array of clusters, with an ID and the data points belonging to it.