kmeans-ts/README.md

A fast, efficient k-means clustering implementation in TypeScript

# K-Means-TS

💹 [K-means](https://en.wikipedia.org/wiki/K-means_clustering) and [k-means++](https://en.wikipedia.org/wiki/K-means%2B%2B) clustering implementation. A Typescript rewrite of [Skmeans-JS](https://github.com/solzimer/skmeans#readme)

## Quick Start

### Installation

```
npm i kmeans-ts
```

### Importation

```typescript
import kmeans from "kmeans-ts";
```

If you want to access the interfaces or utilities within the package, use

```typescript
import { KMeans, Vectors, Utils } from "kmeans-ts";
```

### Implementation


```typescript
var input_data: Array<Array<number>> = [
	[1, 12, 14, 4, 25, 35, 22, 3, 14, 5, 51, 2, 23, 24, 15],
	[7, 34, 15, 34, 17, 11, 34, 2, 35, 18, 52, 34, 33, 21],
	[5, 19, 35, 17, 35, 18, 12, 45, 23, 56, 23, 45, 16, 3]
];
var output: Array<Array<number>> = kmeans(input_data, 3, "kmeans");
```

Returns

```typescript
{
	"iterations": 1,
	"k": 3,
	"indexes": [2,1,0],
	"centroids": [
		[5,19,35,17,35,18,12,45,23,56,23,45,16,3,0],
		[7,34,15,34,17,11,34,2,35,18,52,34,33,21,0],
		[1,12,14,4,25,35,22,3,14,5,51,2,23,24,15]
	]
}
```

## Functionality & Params

| Param        | Description                                                                                                                    | Sample Type                             | Required |
| ------------ | ------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------- | -------- |
| `Input Data` | Array of values to be clustered. Can be multi-dimensional                                                                      | `Array<number>`, `Array<Array<number>>` | Yes      |
| `K`          | Num clusters                                                                                                                   | `number`                                | Yes      |
| `Centroids`  | Initializes centroids. `Kmeans` for random, `Kmeans++` for the K-means++ algorithm. Will attempt to find them if not provided. | `String`                                | Optional |
| `Iterations` | Max num of iterations. Default is `10000`                                                                                      | `number`                                | Optional |

Returns the following object:

| Return value | Description                                     | Sample type            |
| ------------ | ----------------------------------------------- | ---------------------- |
| `Iterations` | Num iterations undergone                        | `number`               |
| `K`          | Num clusters                                    | `number`               |
| `Centroids`  | Centroid values for each cluster                | `Array<number>`        |
| `Indexes`    | Index of centroid for each value of input array | `Array<Array<number>>` |


## Further Examples

```typescript
// K-means w/ 4 clusters & random centroid initialization
var kmeans: KMeans = kmeans(input_data, 4, "kmeans");

// K-means w/ 3 clusters & initial centroids included
var kmeans: KMeans = kmeans(input_data, 3, [
	[3, 1, 5],
	[7, 2, 6],
	[3, 8, 6]
]);

// K-means++ w/ 5 clusters
var kmeans: KMeans = kmeans(input_data, 5, "kmeans++");

// K-means w/ 7 clusters, random centroids, and 15 max iterations
var kmeans: KMeans = kmeans(input_data, 7, null, 15);
```

K-Means-TS can be seen in [MTG-Meta-TS](https://github.com/GoldinGuy/MTGMeta-TS)

## Development Setup

Simply clone the repository, then if you would like to generate a new `ts-config` run

```
--ts-config init
```

This will create a `tsconfig.json` file. If you are using VSCode, enter `Ctrl-Shift-B` and then `tsc:watch`, which will auto-compile TS to JS. You can also use `tsc <filename>` to compile from ts to js.

This project uses [tsdx](https://tsdx.io/) for compilation and minification. You can run that with `npm start`

To test this project, you can navigate to `/example` and run the testing ground with either `ts-node testing_ground.ts`, or by compiling it to JS and then running it in the terminal with `node testing_ground.js`

Alternatively, you can install the awesome VSCode extension [Code Runner](https://marketplace.visualstudio.com/items?itemName=formulahendry.code-runner), which is very convenient


## Contributing

1. Fork K-Means-TS [here](https://github.com/GoldinGuy/K-Means-TS/fork)
2. Create a feature branch (`git checkout -b feature/fooBar`)
3. Commit your changes (`git commit -am 'Add some fooBar'`)
4. Push to the branch (`git push origin feature/fooBar`)
5. Create a new Pull Request

## Meta

Adapted from [@Solzimer's](https://github.com/solzimer) [Skmeans-JS](https://github.com/solzimer/skmeans#readme) by [@GoldinGuy](https://github.com/GoldinGuy)

Distributed under the MIT license. See [LICENSE](https://github.com/GoldinGuy/K-Means-TS/blob/master/LICENSE) for more information.