kNN（k-Nearest Neighbors）JavaScript实现
一个简单的demo
可以通过浏览器开发者工具或者node执行：
// Key terminology: // training set has training examples (features + target variable) // In the classification problem the target variables are called classes // test set // knowledge representation function makeTrainingSet(dimension_of_feature, num_of_examples) { let result = []; for (let i = 0; i != num_of_examples; ++i) { let example = { features: [], label: Math.floor(Math.random() * 3), } for (let j = 0; j != dimension_of_feature; ++j) { example.features[j] = Math.random() * 10 } result.push(example) } return result } let trainingSet = makeTrainingSet(3, 20) // 模拟训练集; 特征向量维数为3; 数据量为20 console.log(trainingSet) let features = makeTrainingSet(3, 1)[0].features // 此条数据用于测试 console.log(features) function getDistance(f1, f2) { const DIMENSION = f1.length // 将距离定义为欧氏距离 let sumOfSquares = 0 for (let i = 0; i != DIMENSION; ++i) { sumOfSquares += Math.pow(f1[i] - f2[i], 2) } return Math.sqrt(sumOfSquares) } function getKNearestNeighbors(features, k, trainingSet) { // 返回值: 数组; k个距离最近的邻居; 对象属性为【距离+标签】 // 参数: k 邻居个数 ; features 未知数据的特征向量 ; trainingSet 已经贴了标签的数据集 let distanceSet = trainingSet.map(training_example => { let distance = getDistance(features, training_example.features) return { distance: distance, label: training_example.label, } }) distanceSet.sort((a, b) => a.distance - b.distance) return distanceSet.slice(0, k) } console.log(getKNearestNeighbors(features, 5, trainingSet))
输出示例：
制作模拟数据测试算法
①纯JS版
数据示例：
生成数据：
<!DOCTYPE html> <html> <head> <meta charset="utf-8" /> <title>ECharts</title> <!-- 引入刚刚下载的 ECharts 文件 --> <script src="echarts.js"></script> <style> main { /*对子元素开启弹性布局*/ display: flex; /*弹性元素在必要的时候换行*/ flex-wrap: wrap; /*将弹性元素居中*/ justify-content: center; } </style> </head> <body> <main> </main> <script type="text/javascript"> // 获取一个[0,val)区间内的随机数 function getRd(val) { return Math.random() * val } //制作二维模拟数据 //以(0,0)到(10,10)构成正方形,标签0为左下,标签1为右下,标签2为右上,标签3为左上 function make2DTrainingSet(num_of_examples) { let result = []; for (let i = 0; i != num_of_examples; ++i) { let example = { features: [], label: Math.floor(getRd(4)), } if (example.label === 0) { example.features[0] = getRd(5) example.features[1] = getRd(5) } else if (example.label === 1) { example.features[0] = 5 + getRd(5) example.features[1] = getRd(5) } else if (example.label === 2) { example.features[0] = 5 + getRd(5) example.features[1] = 5 + getRd(5) } else { example.features[0] = getRd(5) example.features[1] = 5 + getRd(5) } result.push(example) } return result } let trainingSet = make2DTrainingSet(100) console.log(trainingSet) const WIDTH = 600; const HEIGHT = 400; // main用来放div1 let container = document.querySelector('main') let myDiv = createDiv(WIDTH, HEIGHT) container.appendChild(myDiv) let chart = echarts.init(myDiv) chart.setOption({ xAxis: {}, yAxis: {}, series: [ { type: 'scatter', data: trainingSet.filter(x => x.label === 0).map(x => x.features), }, { type: 'scatter', data: trainingSet.filter(x => x.label === 1).map(x => x.features), }, { type: 'scatter', data: trainingSet.filter(x => x.label === 2).map(x => x.features), }, { type: 'scatter', data: trainingSet.filter(x => x.label === 3).map(x => x.features), }, ] }) function createDiv(width, height, display = 'block') { let result = document.createElement('div') result.style.width = width + 'px' result.style.height = height + 'px' // result.style.display = display return result } function makeDate(dataSize) { let result = []; for (let i = 0; i != dataSize; ++i) { result.push({ time: "t" + i, data: Math.random(), }) } return result; } </script> </body> </html>
完整代码：
// 调整参数 const TRAINING_SET_SIZE = 200 const TEST_SET_SIZE = 100 const K = 15 // 获取一个[0,val)区间内的随机数 function getRd(val) { return Math.random() * val } //制作二D模拟数据 //以(0,0)到(10,10)构成正方形,标签0为左下,标签1为右下,标签2为右上,标签3为左上 function make2DTrainingSet(num_of_examples) { let result = []; for (let i = 0; i != num_of_examples; ++i) { let example = { features: [], label: Math.floor(getRd(4)), } if (example.label === 0) { example.features[0] = getRd(5) example.features[1] = getRd(5) } else if (example.label === 1) { example.features[0] = 5 + getRd(5) example.features[1] = getRd(5) } else if (example.label === 2) { example.features[0] = 5 + getRd(5) example.features[1] = 5 + getRd(5) } else { example.features[0] = getRd(5) example.features[1] = 5 + getRd(5) } result.push(example) } return result } function getDistance(f1, f2) { const DIMENSION = f1.length // 将距离定义为欧氏距离 let sumOfSquares = 0 for (let i = 0; i != DIMENSION; ++i) { sumOfSquares += Math.pow(f1[i] - f2[i], 2) } return Math.sqrt(sumOfSquares) } function getKNearestNeighbors(features, k, trainingSet) { // 返回值: 数组; k个距离最近的邻居; 对象属性为【距离+标签】 // 参数: k 邻居个数 ; features 未知数据的特征向量 ; trainingSet 已经贴了标签的数据集 let distanceSet = trainingSet.map(training_example => { let distance = getDistance(features, training_example.features) return { distance: distance, label: training_example.label, } }) distanceSet.sort((a, b) => a.distance - b.distance) return distanceSet.slice(0, k) } function getTargetVariable(features, k, trainingSet) { let neighbors = getKNearestNeighbors(features, k, trainingSet) // console.log(neighbors) let myMap = new Map(); neighbors.forEach(x => { if (myMap.get(x.label)) { myMap.set(x.label, myMap.get(x.label) + 1) } else { myMap.set(x.label, 1) } }); // console.log(myMap) let result let max = 0 myMap.forEach((val, key) => { if (val > max) { result = key max = val } }) return result } let trainingSet = make2DTrainingSet(TRAINING_SET_SIZE) let testSet = make2DTrainingSet(TEST_SET_SIZE) let correct = 0 for (let i = 0; i != testSet.length; ++i) { let testExample = testSet[i] let pv = getTargetVariable(testExample.features, K, trainingSet) if (pv == testExample.label) { correct++ } else { console.log('========W A=========') console.log(testExample.label + ' 预测成 ' + pv) console.log('features: ', testExample.features) console.log('====================') } } console.log('training set size:', TRAINING_SET_SIZE) console.log('k:', K) console.log('correct/total:', correct, TEST_SET_SIZE) console.log('accurate: ', correct / testSet.length)
输出示例：
②图示版
<!DOCTYPE html> <html> <head> <meta charset="utf-8" /> <title>ECharts</title> <!-- 引入刚刚下载的 ECharts 文件 --> <script src="echarts.js"></script> <style> main { /*对子元素开启弹性布局*/ display: flex; /*弹性元素在必要的时候换行*/ flex-wrap: wrap; /*将弹性元素居中*/ justify-content: center; } </style> </head> <body> <main> </main> <script> // 调整参数 const TRAINING_SET_SIZE = 200 const TEST_SET_SIZE = 100 const K = 20 // 获取一个[0,val)区间内的随机数 function getRd(val) { return Math.random() * val } //制作二D模拟数据 //以(0,0)到(10,10)构成正方形,标签0为左下,标签1为右下,标签2为右上,标签3为左上 function make2DTrainingSet(num_of_examples) { let result = []; for (let i = 0; i != num_of_examples; ++i) { let example = { features: [], label: Math.floor(getRd(4)), } if (example.label === 0) { example.features[0] = getRd(5) example.features[1] = getRd(5) } else if (example.label === 1) { example.features[0] = 5 + getRd(5) example.features[1] = getRd(5) } else if (example.label === 2) { example.features[0] = 5 + getRd(5) example.features[1] = 5 + getRd(5) } else { example.features[0] = getRd(5) example.features[1] = 5 + getRd(5) } result.push(example) } return result } function getDistance(f1, f2) { const DIMENSION = f1.length // 将距离定义为欧氏距离 let sumOfSquares = 0 for (let i = 0; i != DIMENSION; ++i) { sumOfSquares += Math.pow(f1[i] - f2[i], 2) } return Math.sqrt(sumOfSquares) } function getKNearestNeighbors(features, k, trainingSet) { // 返回值: 数组; k个距离最近的邻居; 对象属性为【距离+标签】 // 参数: k 邻居个数 ; features 未知数据的特征向量 ; trainingSet 已经贴了标签的数据集 let distanceSet = trainingSet.map(training_example => { let distance = getDistance(features, training_example.features) return { distance: distance, label: training_example.label, } }) distanceSet.sort((a, b) => a.distance - b.distance) return distanceSet.slice(0, k) } function getTargetVariable(features, k, trainingSet) { let neighbors = getKNearestNeighbors(features, k, trainingSet) let myMap = new Map(); neighbors.forEach(x => { if (myMap.get(x.label)) { myMap.set(x.label, myMap.get(x.label) + 1) } else { myMap.set(x.label, 1) } }); let result let max = 0 myMap.forEach((val, key) => { if (val > max) { result = key max = val } }) return result } let trainingSet = make2DTrainingSet(TRAINING_SET_SIZE) let testSet = make2DTrainingSet(TEST_SET_SIZE) let correct = 0 let fail = [] for (let i = 0; i != testSet.length; ++i) { let testExample = testSet[i] let pv = getTargetVariable(testExample.features, K, trainingSet) if (pv == testExample.label) { correct++ } else { console.log('========W A=========') fail.push(testExample.features) console.log(testExample.label + ' 预测成 ' + pv) console.log('features: ', testExample.features) console.log('====================') } } console.log('training set size:', TRAINING_SET_SIZE) console.log('k:', K) console.log('correct/total:', correct, TEST_SET_SIZE) console.log('accurate: ', correct / testSet.length) </script> <!-- 展示数据 --> <script type="text/javascript"> const WIDTH = 600; const HEIGHT = 400; // main用来放div1 let container = document.querySelector('main') let myDiv = createDiv(WIDTH, HEIGHT) container.appendChild(myDiv) let chart = echarts.init(myDiv) chart.setOption({ xAxis: {}, yAxis: {}, series: [ { type: 'scatter', data: trainingSet.filter(x => x.label === 0).map(x => x.features), }, { type: 'scatter', data: trainingSet.filter(x => x.label === 1).map(x => x.features), }, { type: 'scatter', data: trainingSet.filter(x => x.label === 2).map(x => x.features), }, { type: 'scatter', data: trainingSet.filter(x => x.label === 3).map(x => x.features), }, { type: 'scatter', data: fail, }, ] }) function createDiv(width, height, display = 'block') { let result = document.createElement('div') result.style.width = width + 'px' result.style.height = height + 'px' // result.style.display = display return result } function makeDate(dataSize) { let result = []; for (let i = 0; i != dataSize; ++i) { result.push({ time: "t" + i, data: Math.random(), }) } return result; } </script> </body> </html>
输出示例：
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