A tool for data PCA(Principle Component Analysis) and cluster(K-Means & K-Medoids).
To view documentation or get support, visit docs.
To view some examples for more understanding, visit examples:
PCA: ex-PCA.html [source code]
cluster: ex-cluster.html [source code]
cluster with web worker: ex-cluster-webworker.html [source code] * WebWorkers(from blob) does not support IE11.
Note: w-cluster is mainly dependent on
ml-pca,ml-kmeansandk-medoids.
npm i w-cluster
Link: [dev source code]
async function testPCA() {
let mat = [
[40, 50, 60],
[50, 70, 60],
[80, 70, 90],
[50, 60, 80]
]
console.log('mat', mat)
// => mat [ [ 40, 50, 60 ], [ 50, 70, 60 ], [ 80, 70, 90 ], [ 50, 60, 80 ] ]
let resMat = await WCluster.PCA(mat, { nCompNIPALS: 2 })
console.log(resMat)
// => [
// [ -1.704002697669786, 0.43087564048799354 ],
// [ -0.2509699164590232, -1.1519035967558147 ],
// [ 1.9913098008410954, 0.23244503334983269 ],
// [ -0.03633718671228592, 0.48858292291798827 ]
// ]
let mat2 = [
[1040, 50, 60],
[1050, 70, 60],
[1080, 70, 90],
[1050, 60, 80]
]
console.log('mat2', mat2)
// => mat [ [ 1040, 50, 60 ], [ 1050, 70, 60 ], [ 1080, 70, 90 ], [ 1050, 60, 80 ] ]
let resMat2 = await WCluster.PCA(mat2, { nCompNIPALS: 2 })
console.log(resMat2)
// => [
// [ -1.704002697669786, 0.43087564048799354 ],
// [ -0.2509699164590232, -1.1519035967558147 ],
// [ 1.9913098008410954, 0.23244503334983269 ],
// [ -0.03633718671228592, 0.48858292291798827 ]
// ]
let mat3 = [
[11040, 50, 60],
[13050, 70, 60],
[15080, 70, 90],
[17050, 60, 80]
]
console.log('mat3', mat3)
// => mat [ [ 11040, 50, 60 ], [ 13050, 70, 60 ], [ 15080, 70, 90 ], [ 17050, 60, 80 ] ]
let resMat3 = await WCluster.PCA(mat3, { nCompNIPALS: 2 })
console.log(resMat3)
// => [
// [ -1.8599655569892897, 0.4908764271508211 ],
// [ -0.3950941652793108, -1.0977355294143445 ],
// [ 1.3430199944041517, -0.17213692267477554 ],
// [ 0.912039727864449, 0.778996024938299 ]
// ]
}
testPCA()
.catch((err) => {
console.log(err)
})
Link: [dev source code]
async function testCluster() {
let mode = 'k-medoids'
let mat = [
[40, 50, 60],
[50, 70, 60],
[80, 70, 90],
[50, 60, 80]
]
console.log('mat', mat)
// => mat [ [ 40, 50, 60 ], [ 50, 70, 60 ], [ 80, 70, 90 ], [ 50, 60, 80 ] ]
let resMat = await WCluster.cluster(mat, { mode, kNumber: 2, nCompNIPALS: 2 })
console.log(JSON.stringify(resMat, null, 2))
// => {
// "keys": null,
// "ginds": [
// [ 0, 1, 3 ],
// [ 2 ]
// ],
// "gmat": [
// [
// [ -1.704002697669786, 0.43087564048799354 ],
// [ -0.2509699164590232, -1.1519035967558147 ],
// [ -0.03633718671228592, 0.48858292291798827 ]
// ],
// [
// [ 1.9913098008410954, 0.23244503334983269 ]
// ]
// ],
// "gltdt": [
// [
// [ 40, 50, 60 ],
// [ 50, 70, 60 ],
// [ 50, 60, 80 ]
// ],
// [
// [ 80, 70, 90 ]
// ]
// ]
// }
let mat2 = [
[1040, 50, 60],
[1050, 70, 60],
[1080, 70, 90],
[1050, 60, 80]
]
console.log('mat2', mat2)
// => mat [ [ 1040, 50, 60 ], [ 1050, 70, 60 ], [ 1080, 70, 90 ], [ 1050, 60, 80 ] ]
let resMat2 = await WCluster.cluster(mat2, { mode, kNumber: 2, nCompNIPALS: 2 })
console.log(JSON.stringify(resMat2, null, 2))
// => {
// "keys": null,
// "ginds": [
// [ 0, 1, 3 ],
// [ 2 ]
// ],
// "gmat": [
// [
// [ -1.704002697669786, 0.43087564048799354 ],
// [ -0.2509699164590232, -1.1519035967558147 ],
// [ -0.03633718671228592, 0.48858292291798827 ]
// ],
// [
// [ 1.9913098008410954, 0.23244503334983269 ]
// ]
// ],
// "gltdt": [
// [
// [ 1040, 50, 60 ],
// [ 1050, 70, 60 ],
// [ 1050, 60, 80 ]
// ],
// [
// [ 1080, 70, 90 ]
// ]
// ]
// }
let mat3 = [
[11040, 50, 60],
[13050, 70, 60],
[15080, 70, 90],
[17050, 60, 80]
]
console.log('mat3', mat3)
// => mat [ [ 11040, 50, 60 ], [ 13050, 70, 60 ], [ 15080, 70, 90 ], [ 17050, 60, 80 ] ]
let resMat3 = await WCluster.cluster(mat3, { mode, kNumber: 2, nCompNIPALS: 2 })
console.log(JSON.stringify(resMat3, null, 2))
// => {
// "keys": null,
// "ginds": [
// [ 1, 2, 3 ],
// [ 0 ]
// ],
// "gmat": [
// [
// [ -0.3950941652793108, -1.0977355294143445 ],
// [ 1.3430199944041517, -0.17213692267477554 ],
// [ 0.912039727864449, 0.778996024938299 ]
// ],
// [
// [ -1.8599655569892897, 0.4908764271508211 ]
// ]
// ],
// "gltdt": [
// [
// [ 13050, 70, 60 ],
// [ 15080, 70, 90 ],
// [ 17050, 60, 80 ]
// ],
// [
// [ 11040, 50, 60 ]
// ]
// ]
// }
let ltdt = [
{ name: 'Cameron', a: 40, b: 50, c: 60 },
{ name: 'Buckley', a: 50, b: 70, c: 60 },
{ name: 'Paul', a: 80, b: 70, c: 90 },
{ name: 'Fawcett', a: 50, b: 60, c: 80 },
]
console.log('ltdt', ltdt)
// => ltdt [
// { name: 'Cameron', a: 40, b: 50, c: 60 },
// { name: 'Buckley', a: 50, b: 70, c: 60 },
// { name: 'Paul', a: 80, b: 70, c: 90 },
// { name: 'Fawcett', a: 50, b: 60, c: 80 }
// ]
let resLtdt = await WCluster.cluster(ltdt, { mode, kNumber: 2, nCompNIPALS: 2 })
console.log(JSON.stringify(resLtdt, null, 2))
// => {
// "keys": [ "a", "b", "c" ],
// "ginds": [
// [ 0, 1, 3 ],
// [ 2 ]
// ],
// "gmat": [
// [
// [ -1.704002697669786, 0.43087564048799354 ],
// [ -0.2509699164590232, -1.1519035967558147 ],
// [ -0.03633718671228592, 0.48858292291798827 ]
// ],
// [
// [ 1.9913098008410954, 0.23244503334983269 ]
// ]
// ],
// "gltdt": [
// [
// { "name": "Cameron", "a": 40, "b": 50, "c": 60 },
// { "name": "Buckley", "a": 50, "b": 70, "c": 60 },
// { "name": "Fawcett", "a": 50, "b": 60, "c": 80 }
// ],
// [
// { "name": "Paul", "a": 80, "b": 70, "c": 90 }
// ]
// ]
// }
}
testCluster()
.catch((err) => {
console.log(err)
})
Note: w-cluster does not dependent on any package.
[Necessary] Add script for w-cluster.
<!-- for basic -->
<script src="https://cdn.jsdelivr.net/npm/w-cluster@1.0.20/dist/w-cluster.umd.js"></script>
<!-- for web workers -->
<script src="https://cdn.jsdelivr.net/npm/w-cluster@1.0.20/dist/w-cluster.wk.umd.js"></script>