<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>K-Means on DATATWEETS</title><link>https://datatweets.com/tags/k-means/</link><description>Recent content in K-Means on DATATWEETS</description><generator>Hugo</generator><language>en</language><copyright>Copyright (c) 2025 Datatweets</copyright><lastBuildDate>Sun, 05 Jul 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://datatweets.com/tags/k-means/index.xml" rel="self" type="application/rss+xml"/><item><title>Dominant Colors in an Image: Clustering Pixels with K-Means</title><link>https://datatweets.com/blog/dominant-colors-with-kmeans/</link><pubDate>Sun, 05 Jul 2026 00:00:00 +0000</pubDate><guid>https://datatweets.com/blog/dominant-colors-with-kmeans/</guid><description>A first taste of unsupervised learning: there&amp;rsquo;s no label to predict here, just raw pixel data. This post reshapes an image into a table of RGB points, clusters them with scikit-learn&amp;rsquo;s KMeans, and reads the cluster centers back as the image&amp;rsquo;s dominant colors and their prevalence.</description></item></channel></rss>