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Attribute weighting via genetic algorithms for attribute weighted artificial immune system (AWAIS) and its application to heart disease and liver disorders problems

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Title: Attribute weighting via genetic algorithms for attribute weighted artificial immune system (AWAIS) and its application to heart disease and liver disorders problems
Authors: Özşen, Seral seral@selcuk.edu.tr, Güneş, Salih1 sgunes@selcuk.edu.tr
Source: Expert Systems with Applications. Jan2009, Vol. 36 Issue 1, p386-392. 7p.
Subjects: Genetic algorithms, Computer simulation of immune system, Heart diseases, Liver diseases, Pattern perception, Classification, Algorithms, Data
Abstract: An increasing number of algorithms and applications have coming into scene in the field of artificial immune systems (AIS) day by day. Whereas this increase is bringing successful studies, still, AIS is not an effective problem solver in some problem fields such as classification, regression, pattern recognition, etc. So far, many of the developed AIS algorithms have used a distance or similarity measure as the case in instance based learning (IBL) algorithms. The efficiency of IBL algorithms lies mainly in the weighting scheme they used. This weighting idea was taken as the objective of our study in that we used genetic algorithms to determine the weights of attributes and then used these weights in our previously developed Artificial Immune System (AWAIS). We evaluated the performance of new configuration (GA-AWAIS) on two medical datasets which were Statlog Heart Disease and BUPA Liver Disorders dataset. We also compared it with AWAIS for those problems. The obtained classification accuracy was very good with respect to both AWAIS and other common classifiers in literature. [Copyright &y& Elsevier]
Copyright of Expert Systems with Applications is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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PubType: Academic Journal
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  Data: Attribute weighting via genetic algorithms for attribute weighted artificial immune system (AWAIS) and its application to heart disease and liver disorders problems
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  Data: <searchLink fieldCode="AR" term="%22Özşen%2C+Seral%22">Özşen, Seral</searchLink><i> seral@selcuk.edu.tr</i><br /><searchLink fieldCode="AR" term="%22Güneş%2C+Salih%22">Güneş, Salih</searchLink><relatesTo>1</relatesTo><i> sgunes@selcuk.edu.tr</i>
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  Data: <searchLink fieldCode="JN" term="%22Expert+Systems+with+Applications%22">Expert Systems with Applications</searchLink>. Jan2009, Vol. 36 Issue 1, p386-392. 7p.
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  Data: <searchLink fieldCode="DE" term="%22Genetic+algorithms%22">Genetic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+simulation+of+immune+system%22">Computer simulation of immune system</searchLink><br /><searchLink fieldCode="DE" term="%22Heart+diseases%22">Heart diseases</searchLink><br /><searchLink fieldCode="DE" term="%22Liver+diseases%22">Liver diseases</searchLink><br /><searchLink fieldCode="DE" term="%22Pattern+perception%22">Pattern perception</searchLink><br /><searchLink fieldCode="DE" term="%22Classification%22">Classification</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Data%22">Data</searchLink>
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  Data: An increasing number of algorithms and applications have coming into scene in the field of artificial immune systems (AIS) day by day. Whereas this increase is bringing successful studies, still, AIS is not an effective problem solver in some problem fields such as classification, regression, pattern recognition, etc. So far, many of the developed AIS algorithms have used a distance or similarity measure as the case in instance based learning (IBL) algorithms. The efficiency of IBL algorithms lies mainly in the weighting scheme they used. This weighting idea was taken as the objective of our study in that we used genetic algorithms to determine the weights of attributes and then used these weights in our previously developed Artificial Immune System (AWAIS). We evaluated the performance of new configuration (GA-AWAIS) on two medical datasets which were Statlog Heart Disease and BUPA Liver Disorders dataset. We also compared it with AWAIS for those problems. The obtained classification accuracy was very good with respect to both AWAIS and other common classifiers in literature. [Copyright &y& Elsevier]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Expert Systems with Applications is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=34892972
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      – Type: doi
        Value: 10.1016/j.eswa.2007.09.063
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      – Code: eng
        Text: English
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        PageCount: 7
        StartPage: 386
    Subjects:
      – SubjectFull: Genetic algorithms
        Type: general
      – SubjectFull: Computer simulation of immune system
        Type: general
      – SubjectFull: Heart diseases
        Type: general
      – SubjectFull: Liver diseases
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      – SubjectFull: Pattern perception
        Type: general
      – SubjectFull: Classification
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      – SubjectFull: Algorithms
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      – SubjectFull: Data
        Type: general
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      – TitleFull: Attribute weighting via genetic algorithms for attribute weighted artificial immune system (AWAIS) and its application to heart disease and liver disorders problems
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            NameFull: Özşen, Seral
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            NameFull: Güneş, Salih
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              Text: Jan2009
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              Y: 2009
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            – TitleFull: Expert Systems with Applications
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