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Workshop on Engineering Applications

WEA 2016: Applied Computer Sciences in Engineering pp 65–73Cite as

Induction of Rules Based on Similarity Relations for Imbalance Datasets. A Case of Study

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 657))

Abstract

In this paper, the performance of the IRBASIR-Imb algorithm (Induction of Rules Based on Similarity Relations for Imbalance datasets) is used in a classical task in the branch of the Civil Engineering: predict if structural failure depends on the connector (canals) or concrete capacity of connectors. The use of similarity relations allows applying this method in the case of mixed data (features with discrete or real domains). The experimental results show a satisfactory performance of the IRBASIR-Imb algorithm in comparison to others such as C4.5.

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Author information

Authors and Affiliations

  1. Department of Computer Sciences, Universidad de Camagüey, Camagüey, Cuba

    Yaima Filiberto, Mabel Frias & Rafael Larrua

  2. Department of Computer Sciences, Universidad Central “Marta Abreu” de Las Villas, Santa Clara, Cuba

    Rafael Bello

Authors
  1. Yaima Filiberto
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  2. Mabel Frias
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  3. Rafael Larrua
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  4. Rafael Bello
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Corresponding author

Correspondence to Mabel Frias .

Editor information

Editors and Affiliations

  1. Universidad Distrital Francisco José de Caldas, Bogotá, Colombia

    Juan Carlos Figueroa-García

  2. Universidad Distrital Francisco José de Caldas, Bogotá, Colombia

    Eduyn Ramiro López-Santana

  3. Universidad Distrital Francisco José de Caldas, Bogotá, Colombia

    Roberto Ferro-Escobar

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© 2016 Springer International Publishing AG

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Filiberto, Y., Frias, M., Larrua, R., Bello, R. (2016). Induction of Rules Based on Similarity Relations for Imbalance Datasets. A Case of Study. In: Figueroa-García, J., López-Santana, E., Ferro-Escobar, R. (eds) Applied Computer Sciences in Engineering. WEA 2016. Communications in Computer and Information Science, vol 657. Springer, Cham. https://doi.org/10.1007/978-3-319-50880-1_6

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  • DOI: https://doi.org/10.1007/978-3-319-50880-1_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50879-5

  • Online ISBN: 978-3-319-50880-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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