https://github.com/arjunsk/kmeans

Go library implementing Kmeans++ and Elkan's Kmeans algorithm
https://github.com/arjunsk/kmeans

centroid clustering elkan kmeans kmeans-plus-plus

Last synced: 30 days ago
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Go library implementing Kmeans++ and Elkan's Kmeans algorithm

• Host: GitHub
• URL: https://github.com/arjunsk/kmeans
• Owner: arjunsk
• License: apache-2.0
• Created: 2023-10-01T10:00:12.000Z (over 1 year ago)
• Default Branch: master
• Last Pushed: 2024-02-15T21:59:56.000Z (11 months ago)
• Last Synced: 2024-10-16T08:12:07.205Z (3 months ago)
• Topics: centroid, clustering, elkan, kmeans, kmeans-plus-plus
• Language: Go
• Homepage:
• Size: 130 KB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Go Kmeans

[![Go Reference](https://pkg.go.dev/badge/github.com/arjunsk/kmeans/kmeans.svg)](https://pkg.go.dev/github.com/arjunsk/kmeans)

[![Go Report Card](https://goreportcard.com/badge/github.com/arjunsk/kmeans)](https://goreportcard.com/report/github.com/arjunsk/kmeans)

[![Codecov](https://codecov.io/gh/arjunsk/kmeans/branch/master/graph/badge.svg)](https://codecov.io/gh/arjunsk/kmeans)

This is a simple implementation of the [Elkan's Kmeans](https://cdn.aaai.org/ICML/2003/ICML03-022.pdf)

algorithm in Go.

### Installing

```sh

$ go get github.com/arjunsk/kmeans

```

### Usage

```go

package main

import (

	"fmt"

	"github.com/arjunsk/kmeans"

	"github.com/arjunsk/kmeans/elkans"

)

func main() {

	vectorList := [][]float64{

		{1, 2, 3, 4},

		{1, 2, 4, 5},

		{1, 2, 4, 5},

		{1, 2, 3, 4},

		{1, 2, 4, 5},

		{1, 2, 4, 5},

		{10, 2, 4, 5},

		{10, 3, 4, 5},

		{10, 5, 4, 5},

		{10, 2, 4, 5},

		{10, 3, 4, 5},

		{10, 5, 4, 5},

	}

	clusterer, err := elkans.NewKMeans(vectorList, 2,

		500, 0.5,

		kmeans.L2Distance, kmeans.KmeansPlusPlus, false)

	if err != nil {

		panic(err)

	}

	centroids, err := clusterer.Cluster()

	if err != nil {

		panic(err)

	}

	for _, centroid := range centroids {

		fmt.Println(centroid)

	}

	/*

	[1 2 3.6666666666666665 4.666666666666666]

	[10 3.333333333333333 4 5]

	*/

}

```

### FAQ

 Read More 

#### What should be the ideal Centroids Count?

Based on the recommendations from [PGVector](https://github.com/pgvector/pgvector/tree/master#ivfflat) IVF INDEX, 

the idea K should 

> Choose an appropriate number of K - a good place to start is rows / 1000 for up to 1M rows and 

> sqrt(rows) for over 1M rows