k-Nearest Neighbour Classifiers

Files in This Item:
 File SizeFormat
DownloadUCD-CSI-2007-3.pdf759.59 kBAdobe PDF
Title: k-Nearest Neighbour Classifiers
Authors: Cunningham, PádraigDelany, Sarah Jane
Permanent link: http://hdl.handle.net/10197/12360
Date: 27-Mar-2007
Online since: 2021-07-29T16:15:02Z
Abstract: Perhaps the most straightforward classifier in the arsenal or machine learning techniques is the Nearest Neighbour Classifier – classification is achieved by identifying the nearest neighbours to a query example and using those neighbours to determine the class of the query. This approach to classification is of particular importance today because issues of poor run-time performance is not such a problem these days with the computational power that is available. This paper presents an overview of techniques for Nearest Neighbour classification focusing on; mechanisms for assessing similarity (distance), computational issues in identifying nearest neighbours and mechanisms for reducing the dimension of the data.
Type of material: Technical Report
Publisher: University College Dublin. School of Computer Science and Informatics
Series/Report no.: UCD CSI Technical Reports; UCD-CSI-2007-3
Copyright (published version): 2007 the Authors
Keywords: Nearest Neighbour classificationMachine learningComputational complexityDimension reduction
Other versions: https://web.archive.org/web/20080226040105/http:/csiweb.ucd.ie/Research/TechnicalReports.html
Language: en
Status of Item: Not peer reviewed
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Computer Science and Informatics Technical Reports

Show full item record

Page view(s)

Last Week
Last month
checked on Sep 20, 2021


checked on Sep 20, 2021

Google ScholarTM


If you are a publisher or author and have copyright concerns for any item, please email research.repository@ucd.ie and the item will be withdrawn immediately. The author or person responsible for depositing the article will be contacted within one business day.