Classifying heterogeneous data with artificial immune system

Mazidah Puteh, Abdul Razak Hamdan, Khairuddin Omar, Azuraliza Abu Bakar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Artificial Immune System (AIS) is an emerging technique for the classification task and proved to be a reliable technique. In the previous researches, many classifiers including AIS classifiers require the data to be in numerical or categorical data types prior to processing. The transformation of data into any other specific types from their original form can degrade the originality of the data and consume more space and pre processing time. This paper introduces AIS model using clonal selection technique for classifying heterogeneous data in its original types. The model is able to process the data with the types as represented in the database and it solves some problems highlighted in the AIS reviews. To ensure the consistent conditions and fair comparison, the selected algorithms uses the same set of data as used in the proposed model. Experimental results show that this model produces a better accuracy rate than other immune algorithm and comparable to the standard classifiers on most of the benchmark data from UCI Machine Learning Repository.

Original languageEnglish
Title of host publicationProceedings - International Symposium on Information Technology 2008, ITSim
Volume4
DOIs
Publication statusPublished - 2008
EventInternational Symposium on Information Technology 2008, ITSim - Kuala Lumpur
Duration: 26 Aug 200829 Aug 2008

Other

OtherInternational Symposium on Information Technology 2008, ITSim
CityKuala Lumpur
Period26/8/0829/8/08

Fingerprint

Immune system
Classifiers
Processing
Learning systems

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Puteh, M., Hamdan, A. R., Omar, K., & Abu Bakar, A. (2008). Classifying heterogeneous data with artificial immune system. In Proceedings - International Symposium on Information Technology 2008, ITSim (Vol. 4). [4632035] https://doi.org/10.1109/ITSIM.2008.4632035

Classifying heterogeneous data with artificial immune system. / Puteh, Mazidah; Hamdan, Abdul Razak; Omar, Khairuddin; Abu Bakar, Azuraliza.

Proceedings - International Symposium on Information Technology 2008, ITSim. Vol. 4 2008. 4632035.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Puteh, M, Hamdan, AR, Omar, K & Abu Bakar, A 2008, Classifying heterogeneous data with artificial immune system. in Proceedings - International Symposium on Information Technology 2008, ITSim. vol. 4, 4632035, International Symposium on Information Technology 2008, ITSim, Kuala Lumpur, 26/8/08. https://doi.org/10.1109/ITSIM.2008.4632035
Puteh M, Hamdan AR, Omar K, Abu Bakar A. Classifying heterogeneous data with artificial immune system. In Proceedings - International Symposium on Information Technology 2008, ITSim. Vol. 4. 2008. 4632035 https://doi.org/10.1109/ITSIM.2008.4632035
Puteh, Mazidah ; Hamdan, Abdul Razak ; Omar, Khairuddin ; Abu Bakar, Azuraliza. / Classifying heterogeneous data with artificial immune system. Proceedings - International Symposium on Information Technology 2008, ITSim. Vol. 4 2008.
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