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September 28, 2025Journal of Physics Conference SeriesOpen Access

Adaptive Three-Way Density Peak Clustering Integrating Natural Neighbor Structure and Granular-Ball Structure

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Authors

CYChai YanHGHuan Gou

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Overview

Algorithm NWGB-DPC enhances clustering performance in various densities, integrating natural neighbor structure and granular-ball modeling.

Key Points

  • NWGB-DPC significantly improves clustering adaptability and performance.
  • The algorithm effectively integrates natural neighbor structure and granular-ball modeling for better results.
  • Extensive testing on UCI datasets confirms NWGB-DPC as a state-of-the-art clustering approach.
  • The three-way decision framework allows precise object partitioning into core and boundary regions.

Cite This Study

Yan et al. (2025) studied this question.

synapsesocial.com/papers/68d9051b41e1c178a14f4cb7https://doi.org/10.1088/1742-6596/3108/1/012030
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Density peak clustering algorithm based on weighted mutual K-nearest neighbors2025
  2. 2An Improved Density Peak Clustering with Flexible Manifold Distance and Natural Nearest Neighbors for Network Intrusion Detection2024
  3. 3A mutual nearest neighbor search algorithm based on dynamic neighborhood2024
  4. 4Density Peaks Clustering Based on Weighted Density Estimating and Multicluster Merging2025 · 1 citations
  5. 5A Novel Density Peaks Clustering based on Support Point and Nearest Neighbor Relationship2026