Lecture

K-means Clustering: Lloyd's Algorithm and RGB Space

In course

Nostrud eiusmod id nulla ut duis voluptate dolore ipsum quis. Laboris aliquip ullamco laboris elit sint. Non occaecat in adipisicing ad do pariatur in.

Description

This lecture covers the K-means method, focusing on minimizing intra-cluster variance using Lloyd's algorithm. It explains the step-by-step process of assigning observations to clusters and recalculating centroids. The application of K-means in color clustering for image segmentation is also discussed, illustrating how pixels are assigned to clusters based on RGB values.

Instructor

commodo consequat veniam aute

Excepteur eu veniam in nostrud ullamco. Esse laboris proident aliquip nulla esse sit excepteur incididunt. Nostrud laborum enim irure laborum voluptate magna est ad labore laborum dolore. Irure adipisicing esse nisi occaecat nisi aliqua aute amet. Ipsum duis consectetur qui labore veniam. Amet tempor dolore incididunt occaecat nostrud nulla excepteur.

Official source

https://mediaspace.epfl.ch/media/0_aogkqcgu

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Ontological neighbourhood

Information engineering

Machine learning: Unsupervised learning

Related lectures (35)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.