Package Exports
- kmeans-engine
This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (kmeans-engine) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.
Readme
KMeans Engine
This k-means javascript implementation is optimised for large and sparse data set by using an array of objects to represent a sparse matrix.
Most of the other implementations available in npm take a N x M matrix (a 2d array) as input. However, if the data matrix is sparse, it would consumed a lot of memory when creating the N x M matrix. For example, td-idf vectors of text documents actually form a very large and sparse matrix. It will take much time to allocate the 2d array and will even quit if there is not enough memory.
Installation
npm install kmeans-engine
What's New
1.5.0
Upgrade dependencies to fix security alerts
1.4.0
Support options to provide initial centroids. See details in pull request
1.3.0
Update to newer version of vector-object
1.2.0
Support maxIterations parameter in options
1.1.0
Updated to a newer version of vector-object
Usage
const kmeans = require('kmeans-engine');
// array of objects
// engineers and their skills level
const engineers = [
// frontend engineers
{ html: 5, angular: 5, react: 3, css: 3 },
{ html: 4, react: 5, css: 4 },
{ html: 4, react: 5, vue: 4, css: 5 },
{ html: 3, angular: 3, react: 4, vue: 2, css: 3 },
// backend engineers
{ nodejs: 5, python: 3, mongo: 5, mysql: 4, redis: 3 },
{ java: 5, php: 4, ruby: 5, mongo: 3, mysql: 5 },
{ python: 5, php: 4, ruby: 3, mongo: 5, mysql: 4, oracle: 4 },
{ java: 5, csharp: 3, oracle: 5, mysql: 5, mongo: 4 },
// mobile engineers
{ objc: 3, swift: 5, xcode: 5, crashlytics: 3, firebase: 5, reactnative: 4 },
{ java: 4, swift: 5, androidstudio: 4 },
{ objc: 5, java: 4, swift: 3, androidstudio: 4, xcode: 4, firebase: 4 },
{ objc: 3, java: 5, swift: 3, xcode: 4, apteligent: 4 },
// devops
{ docker: 5, kubernetes: 4, aws: 4, ansible: 3, linux: 4 },
{ docker: 4, marathon: 4, aws: 4, jenkins: 5 },
{ docker: 3, marathon: 4, heroku: 4, bamboo: 4, jenkins: 4, nagios: 3 },
{ marathon: 4, heroku: 4, bamboo: 4, jenkins: 4, linux: 3, puppet: 4, nagios: 5 }
];
// accepted options:
// k: number of clusters
// maxIterations (optional): max number of iterations
// initialCentroids (optional): an array of initial centroids in length of k
// debug (optional): show debug message in console or not, default is false
kmeans.clusterize(engineers, { k: 4, maxIterations: 5, debug: true }, (err, res) => {
console.log('----- Results -----');
console.log(`Iterations: ${res.iterations}`);
console.log('Clusters: ');
console.log(res.clusters);
});
/*
----- Results -----
Iterations: 3
Clusters:
[
{
centroid: { docker: 3, kubernetes: 1, aws: 2, ansible: 0.75, linux: 1.75, marathon: 3, jenkins: 3.25,heroku: 2, bamboo: 2, nagios: 2, puppet: 1 },
vectorIds: [ 12, 13, 14, 15 ]
},
{
centroid: { nodejs: 1.25, python: 2, mongo: 4.25, mysql: 4.5, redis: 0.75, java: 2.5, php: 2, ruby: 2, oracle: 2.25, csharp: 0.75 },
vectorIds: [ 4, 5, 6, 7 ]
},
{
centroid: { objc: 2.75, swift: 4, xcode: 3.25, crashlytics: 0.75, firebase: 2.25, reactnative: 1, java: 3.25, androidstudio: 2, apteligent: 1 },
vectorIds: [ 8, 9, 10, 11 ]
},
{
centroid: { html: 4, angular: 2, react: 4.25, css: 3.75, vue: 1.5 },
vectorIds: [ 0, 1, 2, 3 ]
}
]
*/Test
npm install
npm run testTo-Dos
- enhance initial centroid picking
- speed optimisation