Accelerating Immunos 99

Paul Taylor, Fiona A.C. Polack, Jon Timmis

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

2 Citations (SciVal)

Abstract

Immunos 99 is a classification algorithm based upon the principles of Artificial Immune Systems (AIS). AIS algorithms can provide alternatives to classical techniques such as decision trees for classification tasks. Immunos 99 provides one alternative however the algorithm and implementations have some room for performance improvement. This paper discusses improvements made to Immunos 99 and its reference implementation to improve runtime performance. The new algorithm/implementation results in an approximate 40% reduction in run time on test data. The paper closes with a proposal for an implementation of the Immunos 99 algorithm that is suitable for use on map/reduce clusters.

Original languageEnglish
Title of host publicationProceedings of the 12th European Conference on the Synthesis and Simulation of Living Systems
Subtitle of host publicationAdvances in Artificial Life, ECAL 2013
PublisherMIT Press Journals
Pages893-898
Number of pages6
ISBN (Electronic)9780262317092
DOIs
Publication statusPublished - 2013
Event12th European Conference on the Synthesis and Simulation of Living Systems: Advances in Artificial Life, ECAL 2013 - Sicily, Italy
Duration: 02 Sept 201306 Sept 2013

Publication series

NameProceedings of the 12th European Conference on the Synthesis and Simulation of Living Systems: Advances in Artificial Life, ECAL 2013

Conference

Conference12th European Conference on the Synthesis and Simulation of Living Systems: Advances in Artificial Life, ECAL 2013
Country/TerritoryItaly
CitySicily
Period02 Sept 201306 Sept 2013

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