Category Utility

This library allows to clusterize a dataset of purely categorical data by using as a measure of fitness the Category Utility.

You can read more about this value on wikipedia. In a nutshell, it tries to maximize the similarity between items in the same cluster, and minimize the one between different clusters.

API

The function clusterize accepts up to 4 parameters and returns an array of arrays of Point:

data: Point[]

The array of objects with categorical values to be clusterized. It won't be modified.

clusters: number

The desired number of clusters. They all will start with one item each.

weights: Weights - optional

You can set the weight for each object key, so that while clustering you'll be able to force the function to rely more on some values than others.

filteredValues: string[] - optional

Just like setting the weights for those values to 0, it will not use those object keys while clusterizing.

Example

import { clusterize } from 'category-utility'
 
const data = [
  { id: '1', size: 'small', color: 'red' },
  { id: '2', size: 'medium', color: 'blue' },
  { id: '3', size: 'large', color: 'red' },
  { id: '4', size: 'medium', color: 'red' },
  { id: '5', size: 'medium', color: 'red' },
  { id: '6', size: 'medium', color: 'blue' },
  { id: '7', size: 'small', color: 'blue' },
]
 
const weights = { size: 0.5, color: 2 }
const filteredValues = ['id']
const clusters = clusterize(data, 2, weights, filteredValues)
 
// [ [ { id: '1', size: 'small', color: 'red' },
//     { id: '3', size: 'large', color: 'red' },
//     { id: '4', size: 'medium', color: 'red' },
//     { id: '5', size: 'medium', color: 'red' } ],
//   [ { id: '2', size: 'medium', color: 'blue' },
//     { id: '6', size: 'medium', color: 'blue' },
//     { id: '7', size: 'small', color: 'blue' } ] ]