https://github.com/mljs/regression
Regression algorithms
https://github.com/mljs/regression
Last synced: 3 months ago
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Regression algorithms
- Host: GitHub
- URL: https://github.com/mljs/regression
- Owner: mljs
- License: mit
- Created: 2015-02-18T15:49:18.000Z (over 10 years ago)
- Default Branch: main
- Last Pushed: 2024-10-17T08:09:11.000Z (8 months ago)
- Last Synced: 2025-03-28T19:08:10.148Z (3 months ago)
- Language: JavaScript
- Homepage:
- Size: 1.33 MB
- Stars: 44
- Watchers: 15
- Forks: 6
- Open Issues: 12
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
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README
# ml-regression
[![NPM version][npm-image]][npm-url]
[![build status][travis-image]][travis-url]
[![npm download][download-image]][download-url]
Regression algorithms.
## Installation
`$ npm install ml-regression`
## Examples
### Simple linear regression
```js
const SLR = require("ml-regression").SLR;
let inputs = [80, 60, 10, 20, 30];
let outputs = [20, 40, 30, 50, 60];
let regression = new SLR(inputs, outputs);
regression.toString(3) === "f(x) = - 0.265 * x + 50.6";
```
#### External links
Check this cool blog post for a detailed example:
https://hackernoon.com/machine-learning-with-javascript-part-1-9b97f3ed4fe5
### Polynomial regression
```js
const PolynomialRegression = require("ml-regression").PolynomialRegression;
const x = [50, 50, 50, 70, 70, 70, 80, 80, 80, 90, 90, 90, 100, 100, 100];
const y = [
3.3, 2.8, 2.9, 2.3, 2.6, 2.1, 2.5, 2.9, 2.4, 3.0, 3.1, 2.8, 3.3, 3.5, 3.0,
];
const degree = 5; // setup the maximum degree of the polynomial
const regression = new PolynomialRegression(x, y, degree);
console.log(regression.predict(80)); // Apply the model to some x value. Prints 2.6.
console.log(regression.coefficients); // Prints the coefficients in increasing order of power (from 0 to degree).
console.log(regression.toString(3)); // Prints a human-readable version of the function.
console.log(regression.toLaTeX());
```
## License
[MIT](./LICENSE)
[npm-image]: https://img.shields.io/npm/v/ml-regression.svg?style=flat-square
[npm-url]: https://npmjs.org/package/ml-regression
[travis-image]: https://img.shields.io/travis/mljs/regression/main.svg?style=flat-square
[travis-url]: https://travis-ci.org/mljs/regression
[download-image]: https://img.shields.io/npm/dm/ml-regression.svg?style=flat-square
[download-url]: https://npmjs.org/package/ml-regression