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A collection of aggregations, such as OWAs, Choquet and Sugeno integrals, etc.

Project description

Fancy Aggregations DOI

Fanzy Aggregations is a package written in python that implements modern functions to aggregate data using Choquet integral, CF12 generalization, Sugeno, etc. More are to come. Our target is to give a wide range of functions to work with and to generate/use different fuzzy measures.

Implemented functions

  • Choquet Integral
  • Choquet Integral CF and CF1,2
  • Sugeno integral and generalizations.
  • Wide range of T-norms (and T-conorms).
  • Implication operators.
  • OWA operators.
  • Penalty functions.
  • MD deviations.
  • N-Overlap functions.


Fancy Aggregations has its own DOI. If you want to cite it, you can use it. In case you prefer to cite a published paper, you can find a comprehensive list of aggregations, implemented with this library in:

Fumanal-Idocin, J., Wang, Y. K., Lin, C. T., Fernández, J., Sanz, J. A., & Bustince, H. (2021). Motor-Imagery-Based Brain-Computer Interface Using Signal Derivation and Aggregation Functions. IEEE Transactions on Cybernetics.

Reference papers

Each file contains the correspondent paper in its header. Here it is the whole list:

[1] A.H. Altalhi, J.I. Forcén, M. Pagola, E. Barrenechea, H. Bustince, Zdenko Takáč, Moderate deviation and restricted equivalence functions for measuring similarity between data, Information Sciences,Volume 501, 2019, Pages 19-29, ISSN 0020-0255, (

[2] Bustince, H., Beliakov, G., Dimuro, G. P., Bedregal, B., & Mesiar, R. (2017). On the definition of penalty functions in data aggregation. Fuzzy Sets and Systems, 323, 1-18.

[3] A. Jurio, M. Pagola, R. Mesiar, G. Beliakov and H. Bustince, "Image Magnification Using Interval Information," in IEEE Transactions on Image Processing, vol. 20, no. 11, pp. 3112-3123, Nov. 2011. doi: 10.1109/TIP.2011.2158227 URL:

[4] Graçaliz Pereira Dimuro, Giancarlo Lucca, Benjamín Bedregal, Radko Mesiar, José Antonio Sanz, Chin-Teng Lin, Humberto Bustince, Generalized CF1F2-integrals: From Choquet-like aggregation to ordered directionally monotone functions, Fuzzy Sets and Systems, Volume 378, 2020, Pages 44-67, ISSN 0165-0114, (

[5] Beliakov, G., Sola, H. B., & Sánchez, T. C. (2016). A practical guide to averaging functions (Vol. 329). Heidelberg: Springer.


  • Numpy

Project details

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Files for Fancy-aggregations, version 1.5.0
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