Customizable DBSCAN clustering for arbitrary datasets
npm install @apr144/dbscanCustomizable DBSCAN clustering for arbirary datasets.
npm install --save @cdxoo/dbscan
``javascript
const dbscan = require('@cdxoo/dbscan');
let simpleResult = dbscan({
dataset: [21,22,23,24, 27,28,29,30, 9001],
epsilon: 1.01,
});
// => {
// clusters: [ [0,1,2,3], [4,5,6,7] ],
// noise: [ 8 ]
//}
let objectResult = dbscan({
dataset: [{ foo: 21 }, { foo: 22 }, { foo: 27 }, { foo: 28 }],
epsilon: 1.1,
distanceFunction: (a,b) => Math.abs(a.foo - b.foo)
});
// => {
// clusters: [ [0,1], [2,3] ],
// noise: []
//}
`
javascript
dbscan({
dataset: [], // An array of datapoints.
// Datapojnts can be anything when you
// use a custom distance function.
epsilon: 1.3, // Maximum distance between datapoints.
// Determine if a datapoint is in a cluster or not.
// Default is 1.0
epsilonCompare: (distance, epsilon) => ( /.../ ),
// Custom function to compare calculated
// distance and epsilon. Must return true/false.
// Default is (dist, e) => (dist < e)
distanceFunction: (a, b) => ( /.../ ),
// Custom function to calculate the distance
// between two datapoints. Must be given when
// working with higher dimensional datasets,
// or datasets whose items are objects.
// The default function only works on
// one-dimensional data points.
// Defaults is (a, b) => Math.abs(a - b)
minimumPoints: 2,
// Threshold of how many points are needed
// in the same neighborhood to form a cluster.
// Default is 2
})
``