Immune network for classifying heterogeneous data

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

Abstract

In the previous AIS research, most of the AIS classifiers use clonal selection and require the data to be in numerical or categorical data types prior to processing. These classifiers ignore the network feature of the immune system that is suitable for classification. Furthermore, 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 resource limited immune network model with hybrid affinity measurement for classifying heterogeneous data in its original types. The model is able to process the data with the types as represented in the database. The paper shows comparisons between the model and the selected existing immune algorithms that also uses the same set of data and parameters. The experimental results show that the immune network model produces a better accuracy rate with shorter classifier on most of the heterogeneous data from University of California, Irvive (UCI) Machine Learning Repository (MLR).

Original languageEnglish
Title of host publicationProceedings - 8th International Conference on Intelligent Systems Design and Applications, ISDA 2008
Pages373-377
Number of pages5
Volume2
DOIs
Publication statusPublished - 2008
Event8th International Conference on Intelligent Systems Design and Applications, ISDA 2008 - Kaohsiung
Duration: 26 Nov 200828 Nov 2008

Other

Other8th International Conference on Intelligent Systems Design and Applications, ISDA 2008
CityKaohsiung
Period26/11/0828/11/08

Fingerprint

Classifiers
Immune system
Processing
Learning systems

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering

Cite this

Puteh, M., Hamdan, A. R., Omar, K., & Abu Bakar, A. (2008). Immune network for classifying heterogeneous data. In Proceedings - 8th International Conference on Intelligent Systems Design and Applications, ISDA 2008 (Vol. 2, pp. 373-377). [4696361] https://doi.org/10.1109/ISDA.2008.242

Immune network for classifying heterogeneous data. / Puteh, Mazidah; Hamdan, Abdul Razak; Omar, Khairuddin; Abu Bakar, Azuraliza.

Proceedings - 8th International Conference on Intelligent Systems Design and Applications, ISDA 2008. Vol. 2 2008. p. 373-377 4696361.

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

Puteh, M, Hamdan, AR, Omar, K & Abu Bakar, A 2008, Immune network for classifying heterogeneous data. in Proceedings - 8th International Conference on Intelligent Systems Design and Applications, ISDA 2008. vol. 2, 4696361, pp. 373-377, 8th International Conference on Intelligent Systems Design and Applications, ISDA 2008, Kaohsiung, 26/11/08. https://doi.org/10.1109/ISDA.2008.242
Puteh M, Hamdan AR, Omar K, Abu Bakar A. Immune network for classifying heterogeneous data. In Proceedings - 8th International Conference on Intelligent Systems Design and Applications, ISDA 2008. Vol. 2. 2008. p. 373-377. 4696361 https://doi.org/10.1109/ISDA.2008.242
Puteh, Mazidah ; Hamdan, Abdul Razak ; Omar, Khairuddin ; Abu Bakar, Azuraliza. / Immune network for classifying heterogeneous data. Proceedings - 8th International Conference on Intelligent Systems Design and Applications, ISDA 2008. Vol. 2 2008. pp. 373-377
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