1.0Glosarixhttps://glosarix.com/en/Team Glosarixhttps://glosarix.com/en/author/adm_glosarix/K-mean Clustering Algorithm - Glosarixrich600338<blockquote class="wp-embedded-content" data-secret="A6NLB9wpOL"><a href="https://glosarix.com/en/glossary/k-mean-clustering-algorithm-en/">K-mean Clustering Algorithm</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://glosarix.com/en/glossary/k-mean-clustering-algorithm-en/embed/#?secret=A6NLB9wpOL" width="600" height="338" title="“K-mean Clustering Algorithm” — Glosarix" data-secret="A6NLB9wpOL" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script>
/*! This file is auto-generated */
!function(d,l){"use strict";l.querySelector&&d.addEventListener&&"undefined"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!/[^a-zA-Z0-9]/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret="'+t.secret+'"]'),o=l.querySelectorAll('blockquote[data-secret="'+t.secret+'"]'),c=new RegExp("^https?:$","i"),i=0;i<o.length;i++)o[i].style.display="none";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute("style"),"height"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):"link"===t.message&&(r=new URL(s.getAttribute("src")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener("message",d.wp.receiveEmbedMessage,!1),l.addEventListener("DOMContentLoaded",function(){for(var e,t,s=l.querySelectorAll("iframe.wp-embedded-content"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute("data-secret"))||(t=Math.random().toString(36).substring(2,12),e.src+="#?secret="+t,e.setAttribute("data-secret",t)),e.contentWindow.postMessage({message:"ready",secret:t},"*")},!1)))}(window,document);
//# sourceURL=https://glosarix.com/wp-includes/js/wp-embed.min.js
</script>
Description: The K-means clustering algorithm is an unsupervised learning technique used to partition a dataset into k distinct clusters. Each cluster is defined by its centroid, which is the mean of all observations belonging to that cluster. The main objective of the algorithm is to minimize the variation within each cluster and maximize the variation […]