28:null 29:["$","title",null,{"children":"K-Means Clustering | Bryan Hughes | Observable"}] 2e:T1182,skmeans = { /*jshint esversion: 6 */ const eudist = Distance.eudist, mandist = Distance.mandist, absdist = Distance.dist, kmrand = ClusterInit.kmrand, kmpp = ClusterInit.kmpp; const MAX = 10000; /** * Inits an array with values */ function init(len,val,v) { v = v || []; for(let i=0;i0; var count = []; if(!initial) { let idxs = {}, z=0; while(ks.length0; while(ks.length0) { let d = data[Math.floor(Math.random()*len)]; let key = multi? d.join("_") : `${d}`; if(!map[key]) { map[key] = true; ks.push(d); } } if(ks.length0; var map = {}; // First random centroid var c = data[Math.floor(Math.random()*len)]; var key = multi? c.join("_") : `${c}`; ks.push(c); map[key] = true; // Retrieve next centroids while(ks.lengtha.pr-b.pr); // Cummulative Probabilities prs[0].cs = prs[0].pr; for(let i=1;i= rnd let idx = 0; while(idx=0)? d : -d;\n\t\t}\n\n\t\treturn sum;\n\t},\n\n\t/**\n\t * Unidimensional distance\n\t */\n\tdist(v1,v2,sqrt) {\n\t\tvar d = Math.abs(v1-v2);\n\t\treturn sqrt? d : d*d;\n\t}\n\n});","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":14,"value":"$2f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W30","stdlib":"1","titling":"auto"}} 2d:"$2c:body"