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A Framework for Selecting the Optimal Technique Suitable for Application in a Data Mining Task

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Future Information Technology

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 276))

Abstract

This paper presents a conceptual framework for selection of data mining technique based on the 8 selection criteria’s: optimization capability, computation complexity, flexibility, interpretability, scalability, ease of problem encoding, autonomy, and accessibility. The framework is suitable for choosing appropriate technique for application in a particular task of data mining. The paper has set the stage for further research work.

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Author information

Authors and Affiliations

  1. Department of Artificial Intelligence, University of Malaya, Kuala Lumpur, Malaysia

    Haruna Chiroma & Sameem Abdul-Kareem

  2. Department of Computer Science, Faculty of Information and Communication Technology, International Islamic University Malaysia, Gombak, Kuala Lumpur, Malaysia

    Adamau Abubakar

Authors
  1. Haruna Chiroma
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  2. Sameem Abdul-Kareem
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  3. Adamau Abubakar
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Corresponding author

Correspondence to Haruna Chiroma .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Seoul University of Science & and Technology (SeoulTech), Seoul, Korea, Republic of (South Korea)

    James J. (Jong Hyuk) Park

  2. SEECS, University of Ottawa, Ottawa, Ontario, Canada

    Ivan Stojmenovic

  3. School of Information and Communication Engineering, Chungbuk National University, Chungbuk, Korea, Republic of (South Korea)

    Min Choi

  4. Department of Languages and Informatics Systems, Polytechnic University of Catalonia, Barcelona, Spain

    Fatos Xhafa

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Chiroma, H., Abdul-Kareem, S., Abubakar, A. (2014). A Framework for Selecting the Optimal Technique Suitable for Application in a Data Mining Task. In: Park, J., Stojmenovic, I., Choi, M., Xhafa, F. (eds) Future Information Technology. Lecture Notes in Electrical Engineering, vol 276. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40861-8_25

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  • DOI: https://doi.org/10.1007/978-3-642-40861-8_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40860-1

  • Online ISBN: 978-3-642-40861-8

  • eBook Packages: EngineeringEngineering (R0)

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