brainstem v0.0.2

Brainstemjs

brainstemjs is machine learning library for javascript.

npm install brainstem

Available Algorithm

Example

K Nearest Neighbors Algorithm

try on google colab https://colab.research.google.com/drive/1dYQ6m1bSl-6EROI5kqAXwBoaXrPx8IyS?usp=sharing

const {KNNeighborClassifier} = require("brainstem")
const {accuracy_score} = require("brainstem/metrics")
const {train_test_split} = require("brainstem/selection")

const x = [40, 65, 75, 80]
const y = ["E","D","B","A"]

const knn = new KNNeighborClassifier(n_neighbors = 1, distance = "manhattan")
const [x_train, x_test, y_train, y_test] = train_test_split(x,y, test_size=0.3)
knn.fit(x_train,y_train)

const y_pred = knn.predict(x_test)
console.log(accuracy_score(y_test, y_pred))

available distance for K Nearest Neighbors | Name | |------| | Euclidean Distance | | Manhattan Distance |

const {PolynomialOrderOne} = require("brainstem")
const x = [1,2,3,4,5]
const y = [5,4,3,2,1]

const regression = new PolynomialOrderOne()
regression.fit(x,y)
const result = regression.getResult()
const pred = regression.predict([5])

console.log(result)
console.log(pred)

Linear Regression Polynomial Order 2

const {PolynomialOrderTwo} = require("brainstem")
const x = [1,2,3,4,5]
const y = [5,4,3,2,1]

const regression = new PolynomialOrderTwo()
regression.fit(x,y)
const result = regression.getResult()
const pred = regression.predict([5])

console.log(result)
console.log(pred)

Real Data

If you want test with real data like read csv file, json or anything else you have to use another library like danfo.js.

"Danfo.js is an open-source, JavaScript library providing high-performance, intuitive, and easy-to-use data structures for manipulating and processing structured data Danfo.js is heavily inspired by the Pandas library and provides a similar interface and API. This means users familiar with the Pandas API can easily use Danfo.js." - https://danfo.jsdata.org/