linear-regression

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

Linear Regression

The lightest function

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

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 :

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

The loudest function

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

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 :

{
  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 }
}

score

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

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 :

0.9999999999999996

cost function

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 :

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 : [email protected]
• 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