ml-hclust

hclust

Hierarchical clustering algorithms in JavaScript.

Installation

npm i ml-hclust

API Documentation

Usage

AGNES

const { agnes } = require('ml-hclust');

const tree = agnes(data, {
  method: 'ward',
});

Implemented algorithms

• AGNES (AGglomerative NESting): Continuously merge nodes that have the least dissimilarity.
• DIANA (Divisive ANAlysis): The process starts at the root with all the points as one cluster and recursively splits the higher level clusters to build the dendrogram.
• BIRCH (Balanced Iterative Reducing and Clustering using Hierarchies): Incrementally construct a CF (Clustering Feature) tree, a hierarchical data structure for multiphase clustering
• CURE (Clustering Using REpresentatives):
• CHAMELEON

Test

npm install
npm test

Authors

• Miguel Asencio
• Michael Zasso

License

MIT

Changelog

3.0.0 (2019-07-16)

Code Refactoring

• make AGNES algorithm closer to R (#11) (1517124)

BREAKING CHANGES

• • use the Lance-Williams algorithm to update cluster distances.

• add other methods that exist in R.
• remove ClusterLeaf class and use an isLeaf property instead.
• remove index array from clusters. Instead, an indexes() method has been added to compute it.
• add a size property to clusters that indicates the number of leaves below it.
• the default method is now 'complete'.
• DIANA has been removed from the package pending rewriting it.