30:Tec2,{ const svgDims = [600,600] const svg = d3.select(DOM.svg(svgDims[0],svgDims[1])).attr("style","background:white;border:1px solid white") const xScale = d3.scaleLinear().domain([-2,20]).range([30,570]) const yScale = d3.scaleLinear().domain([-40,40]).range([570,30]) const xAxis = svg.append("g").attr("transform","translate(0,300)").call(d3.axisBottom(xScale)) const yAxis = svg.append("g").attr("transform",`translate(${xScale(0)},0)`).call(d3.axisLeft(yScale)) d3.selectAll("#table .row").remove() const pathData = d3.line().x(d => xScale(d.x)).y(d => yScale(d.y))(data) const path = svg.append("path") .attr("d",pathData) .attr("stroke","tomato") .attr("stroke-width",2) .attr("fill","none") .attr("opacity",()=>{ return show?1:0 }) for(let i = 0; i < n; i++){ const segment = segments[i] const l = 16/n const regress = ss.linearRegression(segments[i]) const slope = regress.m const intercept = regress.b const left = segments[i][0][0] const right= segments[i][l-1][0] svg.append("line") .attr("x1",xScale(left)) .attr("y1",yScale(slope*left+intercept)) .attr("x2",xScale(right)) .attr("y2",yScale(slope*right+intercept)) .attr("stroke","cornflowerblue") .attr("stroke-width",2) .attr("opacity",()=>{ return show?0:1 }) } for(let i = 0; i < n-1; i++){ const left = segments[i][16/n-1][0] const right = segments[i+1][0][0] const regress1 = ss.linearRegression(segments[i]) const slope1 = regress1.m const intercept1 = regress1.b const regress2 = ss.linearRegression(segments[i+1]) const slope2 = regress2.m const intercept2 = regress2.b svg.append("line") .attr("x1",xScale(left)) .attr("y1",yScale(slope1*left+intercept1)) .attr("x2",xScale(right)) .attr("y2",yScale(slope2*right+intercept2)) .attr("stroke","cornflowerblue") .attr("stroke-width",2) .attr("opacity",()=>{ return show?0:1 }) } let train = [] for(let i = 0;i <= 15; i++){ const circle = svg.append("circle") .attr("r",4) .attr("cx",xScale(pointsTrain[i].x)) .attr("cy",yScale(pointsTrain[i].y)) .attr("opacity",()=>{ return set == 0?1:0 }) train.push(circle) } let test = [] for(let i = 0;i <= 15; i++){ const circle = svg.append("circle") .attr("r",4) .attr("cx",xScale(pointsTest[i].x)) .attr("cy",yScale(pointsTest[i].y)) .attr("fill","none") .attr("stroke","black") .attr("stroke-width",2) .attr("opacity",()=>{ return set == 0?0:1 }) test.push(circle) } let sumSquares = 0 for(let i = 0; i < n; i++){ const l = 16/n const regress = ss.linearRegression(segments[i]) const slope = regress.m const intercept = regress.b for(let j = l*i;j\n th,td{text-align:center;}\n\n \n \n \n \n \n

${tex`\\large rmseTrain`}	${tex`\\large rmseTest`}

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":23,"value":"$30","pinned":false,"hidden":false,"mode":"ojs"},{"id":54,"value":"viewof set = radio({options:[\n {label:\"training set\",value:0},\n {label:\"test set\",value:1}\n],value:0})","pinned":false,"hidden":false,"mode":"ojs"},{"id":70,"value":"viewof n = radio({options:[\n {label:1,value:1},\n {label:2,value:2},\n {label:4,value:4},\n {label:8,value:8},\n],value:1})","pinned":false,"hidden":false,"mode":"ojs"},{"id":28,"value":"html`

Variables and Code

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":30,"value":"slope = {\n b\n return Math.random()*4-2\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":32,"value":"intercept = {\n b\n return Math.random()*10-5\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":48,"value":"sd = Math.random()*2+5","pinned":false,"hidden":false,"mode":"ojs"},{"id":33,"value":"data = {\n const data = []\n for(let i = -2;i <= 20; i++){\n data.push({x:i,y:slope*i+intercept})\n }\n return data\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":45,"value":"pointsTrain = {\n const points = []\n for(let i = 1; i <= 16; i++){\n const y = slope*i+intercept+normal(0,sd)\n if(y > 40){\n points.push({x:i,y:40})\n }else if(y < -40){\n points.push({x:i,y:-40})\n }else{\n points.push({x:i,y:slope*i+intercept+normal(0,sd)})\n }\n }\n return points\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":60,"value":"pointsTest = {\n const points = []\n for(let i = 1; i <= 16; i++){\n const y = slope*i+intercept+normal(0,sd)\n if(y > 40){\n points.push({x:i,y:40})\n }else if(y < -40){\n points.push({x:i,y:-40})\n }else{\n points.push({x:i,y:slope*i+intercept+normal(0,sd)})\n }\n }\n return points\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":69,"value":"segments = {\n const segments = []\n const length = 16/n\n for(let i = 0;i < n; i++){\n const segment = []\n for(let j = length*i;j

Libraries

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":7,"value":"import {slider,button,select,text,radio,checkbox,number} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":9,"value":"d3 = require(\"d3@5\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":10,"value":"ss = require(\"https://unpkg.com/simple-statistics@6.1.0/dist/simple-statistics.min.js\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":13,"value":"stdlib = require( \"https://unpkg.com/@stdlib/stdlib@0.0.32/dist/stdlib-flat.min.js\" )","pinned":false,"hidden":false,"mode":"ojs"},{"id":15,"value":"normal = stdlib.base.random.normal","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W31","stdlib":"1","titling":"auto"}