---
title: "Sampling Utilities in JavaScript with @kanaries/ml"
description: "Split and sample JavaScript arrays for machine learning workflows with the @kanaries/ml Sampling utilities in browser and Node.js applications."
canonical_url: "https://ml.kanaries.net/docs/apis/utils/sampling"
markdown_url: "https://ml.kanaries.net/docs/apis/utils/sampling.md"
---
# Sampling Utilities in JavaScript

## Algorithm overview

Sampling utilities help create subsets and train/test splits from JavaScript arrays. They are useful for small ML experiments, examples, validation flows, and browser-side demos.

## JavaScript implementation

`@kanaries/ml` exports sampling helpers under `utils.Sampling`. The functions work with generic arrays, so feature rows and labels can remain in normal JavaScript data structures.

## Quick start example

```ts
import { utils } from '@kanaries/ml';

const X = [[0], [1], [2], [3], [4]];
const y = [0, 0, 1, 1, 1];

const split = utils.Sampling.trainTestSplit(X, y, {
  testSize: 0.4,
  randomState: 42,
});

const sample = utils.Sampling.std([1, 2, 3, 4, 5], 3);
console.log(sample);
```

## Detailed API reference

```ts
utils.Sampling.std<T>(arr: T[], size: number): T[]
```

Returns a sample without replacement. If `size` is greater than or equal to the array length, it returns a shallow copy.

```ts
utils.Sampling.trainTestSplit<X, Y>(
  X: X[],
  y?: Y[],
  options?: {
    testSize?: number;
    shuffle?: boolean;
    randomState?: number;
  },
): {
  XTrain: X[];
  XTest: X[];
  yTrain?: Y[];
  yTest?: Y[];
}
```

`testSize` can be a fraction less than `1` or an absolute count. `shuffle` defaults to `true`; set `randomState` for repeatable splits.