Visualizing stable/unstable equilibria in K-Means unsupervised learning algorithm. Each run follows the path of the mean converging as shown here
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April 24, 2017 11:28
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Visualizing K-Means equilibria
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| function randomPoints(_num, _dist, _xR, _yR) { | |
| if(arguments.length<2) _dist = 'irwinHall' | |
| if(!_xR||!_yR) { | |
| var xRange = yRange = [0,1] | |
| }else{ | |
| var xRange = d3.range(_xR[0],_xR[1]) | |
| var yRange = d3.range(_yR[0],_yR[1]) | |
| } | |
| if(_dist == 'uniform'){ | |
| x = d3.range(0,_num).map(function () { | |
| return d3.shuffle(xRange)[0] | |
| }) | |
| y = d3.range(0,_num).map(function () { | |
| return d3.shuffle(yRange)[0] | |
| }) | |
| }else{ | |
| x = d3.range(0,_num).map(function () { | |
| if(['bates','irwinHall'].indexOf(_dist)>-1){ | |
| rnd = d3.random[_dist](_dist=='bates'?8:1)() | |
| rnd = Math.round(rnd*d3.max(xRange)) | |
| }else if(_dist=='normal'){ | |
| rnd = d3.random[_dist](d3.mean(xRange),d3.mean(xRange)/3)() | |
| }else if(_dist=='logNormal'){ | |
| rnd = d3.random[_dist]()() | |
| rnd = Math.round(rnd*d3.mean(xRange)/3) | |
| } | |
| return rnd | |
| }).map(function (d) {return Math.abs(d)}) | |
| y = d3.range(0,_num).map(function () { | |
| if(['bates','irwinHall'].indexOf(_dist)>-1){ | |
| rnd = d3.random[_dist](_dist=='bates'?8:1)() | |
| rnd = Math.round(rnd*d3.max(yRange)) | |
| }else if(_dist=='normal'){ | |
| rnd = d3.random[_dist](d3.mean(yRange),d3.mean(yRange)/3)() | |
| }else if(_dist=='logNormal'){ | |
| rnd = d3.random[_dist]()() | |
| rnd = Math.round(rnd*d3.mean(yRange)/3) | |
| } | |
| return rnd | |
| }).map(function (d) {return Math.abs(d)}) | |
| } | |
| return d3.zip(x,y).map(function(d){return {x:d[0],y:d[1]}}) | |
| } | |
| function clusterPoints(numC,numPts,_dist,_xR,_yR){ | |
| var clusters = [] | |
| d3.range(0,numC).forEach(function (i) { | |
| cPts = randomPoints(4,'uniform',_xR,_yR) | |
| c={} | |
| c.dist = _dist | |
| c.xRange = d3.extent(cPts.map(function(p){return p.x})) | |
| c.yRange = d3.extent(cPts.map(function(p){return p.y})) | |
| c.points = randomPoints(numPts,c.dist,c.xRange,c.yRange) | |
| clusters.push(c) | |
| }) | |
| // clusters.reduce(function (prev,curr) {return prev.concat(curr)}) | |
| return clusters | |
| } |
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| <!DOCTYPE html> | |
| <html> | |
| <head> | |
| <meta charset="utf-8"> | |
| <title>K-means</title> | |
| <style media="screen"> | |
| body{ | |
| margin: 0; | |
| } | |
| svg{ | |
| overflow: visible; | |
| } | |
| .test,.actual{ | |
| opacity: .4; | |
| } | |
| .test circle{ | |
| fill:rgba(255, 255, 255, 0); | |
| stroke:#aaa; | |
| stroke-width:1px; | |
| opacity: .5; | |
| } | |
| .lines line{ | |
| stroke:#aaa; | |
| stroke-width:1px; | |
| stroke-opacity:.25; | |
| } | |
| .mean{ | |
| /*opacity: 0;*/ | |
| /*fill:rgba(255, 255, 255, 0);*/ | |
| stroke-width:3px; | |
| } | |
| .meanPath{ | |
| fill:rgba(255, 255, 255, 0); | |
| stroke:#333; | |
| stroke-width:1px; | |
| } | |
| </style> | |
| </head> | |
| <body> | |
| <svg></svg> | |
| </body> | |
| <script src="lodash.min.js"></script> | |
| <script src="/blacki/raw/b83b3d4139257a353b8a/d3.min.js"></script> | |
| <script src="/blacki/raw/b83b3d4139257a353b8a/dat.gui.min.js"></script> | |
| <script src="/blacki/raw/b83b3d4139257a353b8a/d3-jetpack.js"></script> | |
| <script src="/blacki/raw/b83b3d4139257a353b8a/d3-starterkit.js"></script> | |
| <script src="d3-randompoints.js"></script> | |
| <script src="script.js"></script> | |
| </html> |
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