linear-regression

!GitHub CI

Simple linear regression made in JavaScript.

How to install

npm i clementreiffers-linear-regression or yarn add clementreiffers-linear-regression if you
use yarn instead of npm.

How to use

$3

#### The lightest function

the lightest function is very usefull if you're interested in getting only the essential
parameters

``js
import { linearRegression, predict } from "clementreiffers-linear-regression";
// import { computeLightLinearRegression } from "clementreiffers-linear-regression";

const x = [1, 2, 3, 4];
const y = [1, 2, 3, 4];
const lr = linearRegression(x, y, true); // if you want values into an Object

// executed only if true in linearRegression Function, it gives the same result as above
// computeLightLinearRegression(x, y);

const pred1 = predict([1, 2], lr);
const pred2 = predict(6, lr);

console.log(lr); // to show the object which represents the linear regression

`

by trying this example above, you will have :

`text
{ parameters: { a: 1, b: 0 } }
`

#### The loudest function

it will compute all necessary calculations and put it into the same json.

`js
import { linearRegression, predict } from "clementreiffers-linear-regression";
// import { computeLoudLinearRegression } from "clementreiffers-linear-regression";

const x = [1, 2, 3, 4];
const y = [1, 2, 3, 4];
const lr = linearRegression(x, y); // if you want values into an Object

// executed by default, it gives the same result as above
// computeLoudLinearRegression(x, y);

const pred1 = predict([1, 2], lr);
const pred2 = predict(6, lr);

console.log(lr); // to show the object which represents the linear regression

`

by trying this example above, you will have :

`text
{
parameters: { a: 1, b: 0 },
trainData: { x: [ 1, 2, 3, 4 ], y: [ 1, 2, 3, 4 ] },
trainCurvePredict: [ 1, 2, 3, 4 ],
statistics: { r2: 0.9999999999999996, cost: 0, pearson: 0.9999999999999998 }
}
`

$3

the score represents the capacity to do a linear regression with the data given.

`js
import { score } from "clementreiffers-linear-regression";

const x = [1, 2, 3, 4];
const y = [1, 2, 3, 4];

console.log(score(x, y));

`

by executing this code you will have :

`text
0.9999999999999996
`

$3

`js
import { linearRegression, costFunction } from "clementreiffers-linear-regression";

const x = [1, 2, 3, 4];
const y = [1, 2, 3, 4];

const lr = linearRegression(x, y);
const pred = predict(lr, x);

const cost = costFunction(y, pred);
console.log(cost);
`

by executing this function you will have :

`text
0
``

How it is calculated

this package use the Covariance and Variance to calculate the linear regression,
see here : https://en.wikipedia.org/wiki/Linear_regression

Contacts

any idea to improve this package ?

- email me to : clement.reiffers@esme.fr
- do a git issue on 
- contact me on linkedin : https://www.linkedin.com/in/cl%C3%A9ment-reiffers-bb8983185/

Links

See the source code on 

See the package on