{"version":"1.0","provider_name":"Itxperts","provider_url":"https:\/\/itxperts.co.in\/blog","author_name":"@mritxperts","author_url":"https:\/\/itxperts.co.in\/blog\/author\/mritxpertsgmail-com\/","title":"Encoding Categorical Variables: Label vs One-Hot Encoding - Itxperts","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"rcUW4BGrbQ\"><a href=\"https:\/\/itxperts.co.in\/blog\/encoding-categorical-variables-label-vs-one-hot-encoding\/\">Encoding Categorical Variables: Label vs One-Hot Encoding<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/itxperts.co.in\/blog\/encoding-categorical-variables-label-vs-one-hot-encoding\/embed\/#?secret=rcUW4BGrbQ\" width=\"600\" height=\"338\" title=\"&#8220;Encoding Categorical Variables: Label vs One-Hot Encoding&#8221; &#8212; Itxperts\" data-secret=\"rcUW4BGrbQ\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script>\n\/*! This file is auto-generated *\/\n!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);\n\/\/# sourceURL=https:\/\/itxperts.co.in\/blog\/wp-includes\/js\/wp-embed.min.js\n<\/script>\n","description":"When working on Machine Learning models, one common challenge you\u2019ll encounter is handling categorical data. Most ML algorithms work only with numbers, so converting categorical variables (like \u201cGender\u201d, \u201cCity\u201d, or \u201cYes\/No\u201d types) into a numerical format is essential. In this post, we\u2019ll explore two popular encoding techniques: Let\u2019s understand how and when to use each. [&hellip;]","thumbnail_url":"https:\/\/itxperts.co.in\/blog\/wp-content\/uploads\/2025\/05\/cropped-cropped-itxperts_logo.png","thumbnail_width":436,"thumbnail_height":398}