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September 5, 2025

Enhanced Features extraction method based on Fuzzy C-meansalgorithm

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Authors

NHNidhal Hasan HasaanLMLamia AbedNoor Muhammed

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Overview

Observational analysis finds enhanced classification performance using fuzzy c-means clustering, indicating improved feature quality.

Key Points

  • The proposed fuzzy c-means method significantly improved classification performance metrics across multiple datasets.
  • CICIDS2017 dataset achieved an accuracy of 99.10%, while breast cancer dataset scored 96.71%, showcasing effective feature extraction.
  • Analysis employed fuzzy c-means alongside K-means for comparison, highlighting the former's advantages in feature representation.
  • The method's adaptability makes it fit for data with unclear or overlapping class boundaries, enhancing its practical applicability.

Cite This Study

Hasaan et al. (2025) studied this question.

synapsesocial.com/papers/68bb3d682b87ece8dc956ae2https://doi.org/10.31237/osf.io/b3x2k_v1
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