abhisheksoni27

/**
 * https://stackoverflow.com/a/12646864
 * Randomize array element order in-place.
 * Using Durstenfeld shuffle algorithm.
 */
function shuffleArray(array) {
    for (var i = array.length - 1; i > 0; i--) {
        var j = Math.floor(Math.random() * (i + 1));
        var temp = array[i];
        array[i] = array[j];

abhisheksoni27

function dressData() {

    /**
     * There are three different types of Iris flowers
     * that this dataset classifies.
     *
     * 1. Iris Setosa (Iris-setosa)
     * 2. Iris Versicolor (Iris-versicolor)
     * 3. Iris Virginica (Iris-virginica)
     *

abhisheksoni27

function error(predicted, expected) {
    let misclassifications = 0;
    for (var index = 0; index < predicted.length; index++) {
        if (predicted[index] !== expected[index]) {
            misclassifications++;
        }
    }
    return misclassifications;
}

abhisheksoni27

function test() {
    const result = knn.predict(testSetX);
    const testSetLength = testSetX.length;
    const predictionError = error(result, testSetY);
    console.log(`Test Set Size = ${testSetLength} and number of Misclassifications = ${predictionError}`);
    predict();
}

abhisheksoni27

require('brain.js');
require('gpu.js');

//setup environment, ignore
var canvas = document.createElement('canvas');

function specialLogger() {
  out.innerHTML = arguments[0];
}

abhisheksoni27

var A = [
  [
    1, 1
  ],
  [
    1, 1
  ],
  [1, 1]
];

abhisheksoni27

#extension GL_EXT_draw_buffers : require
precision highp float;
precision highp int;
precision highp sampler2D;

const float LOOP_MAX = 100.0;
#define EPSILON 0.0000001;

uniform highp vec3 uOutputDim;
uniform highp vec2 uTexSize;

abhisheksoni27

#extension GL_EXT_draw_buffers : require
precision highp float;
precision highp int;
precision highp sampler2D;

const float LOOP_MAX = 100.0;
#define EPSILON 0.0000001;

uniform highp vec3 uOutputDim;
uniform highp vec2 uTexSize;

abhisheksoni27

const KNN = require('ml-knn');
const csv = require('csvtojson');
const prompt = require('prompt');
let knn;

const csvFilePath = 'iris.csv'; // Data
const names = ['sepalLength', 'sepalWidth', 'petalLength', 'petalWidth', 'type']; // For header

let seperationSize; // To seperate training and test data

abhisheksoni27

function train() {
    knn = new KNN(trainingSetX, trainingSetY, {k: 7});
    test();
}