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The Influence of Induced OWA Operators in a Clustering Method

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Fuzzy Techniques: Theory and Applications (IFSA/NAFIPS 2019 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1000))

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Abstract

In this work we present an adaptation of the well known k-means algorithm for clustering. The proposal increases the flexibility of the algorithm to calculate the representative value of each cluster. To do so, we work with Induced Ordered Weighting Averaging operators. These instances of aggregation functions are able to increase or decrease the influence of the data in the final result depending on the specific values of the weights. We present an experimental study to show how these operators are able to modify the representatives of the clusters. We also compare our results over some standard datasets.

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Acknowledgments

This work is partially supported by the Public University of Navarra under the project PJUPNA13 and by the Spanish Government under the project TIN2016-77356-P (AEI/FEDER, UE).

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Authors and Affiliations

  1. Departamento de Estadistica, Informatica y Matematicas, Universidad Publica de Navarra, Pamplona, Spain

    Aranzazu Jurio, Mikel Sesma-Sara, Jose Antonio Sanz Delgado & Humberto Bustince

Authors
  1. Aranzazu Jurio
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  2. Mikel Sesma-Sara
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  3. Jose Antonio Sanz Delgado
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  4. Humberto Bustince
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Corresponding author

Correspondence to Aranzazu Jurio .

Editor information

Editors and Affiliations

  1. Department of Mathematics, University of Louisiana at Lafayette, Lafayette, LA, USA

    Ralph Baker Kearfott

  2. Center for Computing Research (CIC), Instituto Politecnico Nacional, Ciudad de Mexico, Mexico

    Ildar Batyrshin

  3. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada

    Marek Reformat

  4. Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA

    Martine Ceberio

  5. Department of Computer Science, University of Texas at El Paso , El Paso, TX, USA

    Vladik Kreinovich

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Jurio, A., Sesma-Sara, M., Sanz Delgado, J.A., Bustince, H. (2019). The Influence of Induced OWA Operators in a Clustering Method. In: Kearfott, R., Batyrshin, I., Reformat, M., Ceberio, M., Kreinovich, V. (eds) Fuzzy Techniques: Theory and Applications. IFSA/NAFIPS 2019 2019. Advances in Intelligent Systems and Computing, vol 1000. Springer, Cham. https://doi.org/10.1007/978-3-030-21920-8_3

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