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Optimal Feature Selection for Multivalued Attributes Using Transaction Weights as Utility Scale

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Proceedings of the Second International Conference on Computational Intelligence and Informatics

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 712))

Abstract

Attribute selection procedure is a key step in the process of Knowledge Discovery in Database (KDD). Majority of the earlier contributions of selection methods can handle easier attribute types. Such methods are not for multivalued attributes that comprise multiple values in simultaneously. Majority of the existing attribute selection methods can manage simple attribute types like the numerical and categorical. The methods cannot fit multivalued attributes, which are attributes that constitute multiple values simultaneously in the dataset for same instance. In this manuscript, a contemporary approach for selecting optimal values for features of multivalued attributes is proposed. In the proposed solution, the method is about adaptation of utility mining based pattern discovery approach. For evaluating the proposed approach, experiments are carried out with multivalued and multiclass datasets that are submitted to k-means clustering technique. The experiments show that the proposed method is optimal to assess the relevance of multivalued attributes toward mining models such as clustering.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, AITS, Rajampet, Andhra Pradesh, India

    K. Lnc Prakash

  2. Department of Computer Science and Engineering, GRIET, Hyderabad, Telangana, India

    K. Anuradha

Authors
  1. K. Lnc Prakash
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  2. K. Anuradha
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Correspondence to K. Lnc Prakash .

Editor information

Editors and Affiliations

  1. Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges, Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  2. Departamento de Engenharia Mecânica, Universidade do Porto, Porto, Portugal

    João Manuel R.S. Tavares

  3. Department of Computer Science and Engineering, JNTUH College of Engineering Hyderabad (Autonomous), Hyderabad, Telangana, India

    B. Padmaja Rani

  4. Department of Computer Science and Engineering, JNTUH College of Engineering Hyderabad (Autonomous), Hyderabad, Telangana, India

    V. Kamakshi Prasad

  5. CMR Technical Campus, Hyderabad, Telangana, India

    K. Srujan Raju

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Lnc Prakash, K., Anuradha, K. (2018). Optimal Feature Selection for Multivalued Attributes Using Transaction Weights as Utility Scale. In: Bhateja, V., Tavares, J., Rani, B., Prasad, V., Raju, K. (eds) Proceedings of the Second International Conference on Computational Intelligence and Informatics . Advances in Intelligent Systems and Computing, vol 712. Springer, Singapore. https://doi.org/10.1007/978-981-10-8228-3_49

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  • DOI: https://doi.org/10.1007/978-981-10-8228-3_49

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8227-6

  • Online ISBN: 978-981-10-8228-3

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