Büyük veri kümelerinin yaklaçik spektral öbeklemesi için k-ortalama++ nicemleme yönteminin kullanilmasi

Translated title of the contribution: The use of k-means++ for approximate spectral clustering of large datasets

Berna Yalçin, Kadim Taşdemir

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

Spectral clustering (SC) has been commonly used in recent years, thanks to its nonparametric model, its ability to extract clusters of different manifolds and its easy application. However, SC is infeasible for large datasets because of its high computational cost and memory requirement. To address this challenge, approximate spectral clustering (ASC) has been proposed for large datasets. ASC involves two steps: firstly limited number of data representatives (also known as prototypes) are selected by sampling or quantization methods, then SC is applied to these representatives using various similarity criteria. In this study, several quantization and sampling methods are compared for ASC. Among them, k-means++, which is a recently popular algorithm in clustering, is used to select prototypes in ASC for the first time. Experiments on different datasets indicate that k-means++ is a suitable alternative to neural gas and selective sampling in terms of accuracy and computational cost.

Translated title of the contributionThe use of k-means++ for approximate spectral clustering of large datasets
Original languageTurkish
Title of host publication2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings
PublisherIEEE Computer Society
Pages220-223
Number of pages4
ISBN (Print)9781479948741
DOIs
Publication statusPublished - 2014
Event2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Trabzon, Turkey
Duration: 23 Apr 201425 Apr 2014

Publication series

Name2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings

Conference

Conference2014 22nd Signal Processing and Communications Applications Conference, SIU 2014
Country/TerritoryTurkey
CityTrabzon
Period23/04/1425/04/14

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