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Redescending M-Estimators Analysis on the Intuitionistic Fuzzy Clustering Algorithm for Skin Lesion Delimitation

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Data Analytics and Computational Intelligence: Novel Models, Algorithms and Applications

Part of the book series: Studies in Big Data ((SBD,volume 132))

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Abstract

This study has conducted an investigation of the Redescending M-Estimators as alternative to strengthen an Intuitionistic Fuzzy C-Means algorithm against atypical information. In this regard, the objective function was stated taking into account the loss function, while the update expressions for membership matrix and prototypes vector were formulated by a derivative procedure, depending on the influence functions. The evaluated estimators were Huber Skipped Mean, Simple Cut, Tukey Biweight, Hampel’s Three Part Redescending, Andrew’s Sine, German-MacClure, Lorentzian, Asad-Qadir, Insha and Alamgir. The empirical study was performed using the ISIC 2017 dataset in order to make the skin lesion delimitation task, these images had inherent artifacts that were considered as atypical information; the performance was quantified by popular state-of-the-art metrics. The quantitative results show an outstanding performance of the Hampel’s Three Part Redescending with Jaccard Similarity Coefficient\(\,=0.905\pm 0.054\), Dice Measure\(\,=0.910\pm 0.060\), Misclassification Ratio\(\,=\,7.174\pm 0.864\) and Hausdorff Distance\(\,=6.281\pm 0.804\), in contrast all rest estimators.

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Acknowledgements

The authors thank to CONACYT, as well as TecNM-CENIDET for their financial support.

Author information

Authors and Affiliations

  1. Tecnológico Nacional de México/Centro Nacional de Investigación y Desarrollo Tecnológico, Interior Internado Palmira S/N, Cuernavaca-Morelos, Mexico

    Dante Mújica-Vargas & Alicia Martínez-Rebollar

  2. Unidad Profesional Interdisciplinaria en Ingeniería y Tecnologías Avanzadas, Instituto Politécnico Nacional, Ciudad de México, Mexico

    Blanca Carvajal-Gámez

  3. Sección de Estudios de Posgrado e Investigación, ESIME Azcapotzalco, Instituto Politécnico Nacional, Av. de Las Granjas No. 682, Col., Ciudad de México, Santa Catarina, Mexico

    José de Jesús Rubio

Authors
  1. Dante Mújica-Vargas
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  2. Blanca Carvajal-Gámez
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  3. Alicia Martínez-Rebollar
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  4. José de Jesús Rubio
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Corresponding author

Correspondence to Dante Mújica-Vargas .

Editor information

Editors and Affiliations

  1. División Multidisciplinaria de Ciudad Universitaria, Universidad Autónoma de Ciudad Juárez, Chihuahua, Mexico

    Gilberto Rivera

  2. Tecnológico Nacional de México/Instituto Tecnológico de Ciudad Madero, Ciudad Madero, Tamaulipas, Mexico

    Laura Cruz-Reyes

  3. School of Engineering, Universidad de Cádiz, Cadiz, Spain

    Bernabé Dorronsoro

  4. Universidad Tecnológica de La Habana “José Antonio Echeverría”, La Habana, Cuba

    Alejandro Rosete

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Mújica-Vargas, D., Carvajal-Gámez, B., Martínez-Rebollar, A., Rubio, J.d.J. (2023). Redescending M-Estimators Analysis on the Intuitionistic Fuzzy Clustering Algorithm for Skin Lesion Delimitation. In: Rivera, G., Cruz-Reyes, L., Dorronsoro, B., Rosete, A. (eds) Data Analytics and Computational Intelligence: Novel Models, Algorithms and Applications. Studies in Big Data, vol 132. Springer, Cham. https://doi.org/10.1007/978-3-031-38325-0_6

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