Flexible immune network recognition system for mining heterogeneous data

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

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

4 Citations (Scopus)

Abstract

Artificial Immune System (AIS) is an emerging technique for the classification task and proved to be a reliable technique. In previous studies, 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 immune network 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 bias problems highlighted in the AIS review papers. To ensure the consistent conditions and fair comparison, the selected existing algorithms use the same set of data as used in the proposed model. Experimental results show that this network-based model produces a better accuracy rate than the existing population-based immune algorithm and than the standard classifiers on most of the data from University of California, Irvive (UCI) Machine Learning Repository (MLR) and University of California, Riverside (UCR) Time Series Data (TSR).

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages232-241
Number of pages10
Volume5132 LNCS
DOIs
Publication statusPublished - 2008
Event7th International Conference on Artificial Immune Systems, ICARIS 2008 - Phuket
Duration: 10 Aug 200813 Aug 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5132 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other7th International Conference on Artificial Immune Systems, ICARIS 2008
CityPhuket
Period10/8/0813/8/08

Fingerprint

Data Mining
Immune system
Mining
Immune System
Artificial Immune System
Classifiers
Classifier
Processing
Learning systems
Time series
Databases
Immune Algorithm
Nominal or categorical data
Time Series Data
Model
Repository
Preprocessing
Machine Learning
Population
Experimental Results

Keywords

  • Accuracy
  • Artificial Immune System (AIS)
  • Classification
  • Heterogeneous
  • Immune network
  • Significant difference

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Puteh, M., Hamdan, A. R., Omar, K., & Abu Bakar, A. (2008). Flexible immune network recognition system for mining heterogeneous data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5132 LNCS, pp. 232-241). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5132 LNCS). https://doi.org/10.1007/978-3-540-85072-4_21

Flexible immune network recognition system for mining heterogeneous data. / Puteh, Mazidah; Hamdan, Abdul Razak; Omar, Khairuddin; Abu Bakar, Azuraliza.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5132 LNCS 2008. p. 232-241 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5132 LNCS).

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

Puteh, M, Hamdan, AR, Omar, K & Abu Bakar, A 2008, Flexible immune network recognition system for mining heterogeneous data. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 5132 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5132 LNCS, pp. 232-241, 7th International Conference on Artificial Immune Systems, ICARIS 2008, Phuket, 10/8/08. https://doi.org/10.1007/978-3-540-85072-4_21
Puteh M, Hamdan AR, Omar K, Abu Bakar A. Flexible immune network recognition system for mining heterogeneous data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5132 LNCS. 2008. p. 232-241. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-540-85072-4_21
Puteh, Mazidah ; Hamdan, Abdul Razak ; Omar, Khairuddin ; Abu Bakar, Azuraliza. / Flexible immune network recognition system for mining heterogeneous data. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5132 LNCS 2008. pp. 232-241 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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