Lecture

Support Vector Clustering: SVC

Description

This lecture covers Support Vector Clustering (SVC), where data points are mapped to a high dimensional feature space using a Gaussian kernel. It explains the constraints, Lagrangian, and the solution approach for SVC. The lecture also discusses the distance calculation for query points and the impact of kernel width on clustering.

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.

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.