This is the code of the paper Kernel-Bounded Clustering: Achieving the Objective of Spectral Clustering without Eigendecomposition

Python

pip install kbc-clustering

from kbc import KBC
import numpy as np

X = np.random.rand(1000, 50)
model = KBC(k=5, tau=0.4, psi=64, random_state=42)
labels = model.fit_predict(X)

MATLAB R2023a: codes/demo_nss_kbc.m gives an example of clustering using $NSS$-KBC, and codes/EC_sample.m implements the $NSS$-KBC algorithm.

License.

Hang Zhang and Kai Ming Ting and Ye Zhu. Kernel-Bounded Clustering: Achieving the Objective of Spectral Clustering without Eigendecomposition. Artificial Intelligence.

@article{zhang2025kernel,
  title={Kernel-Bounded Clustering: Achieving the Objective of Spectral Clustering without Eigendecomposition},
  author={Zhang, Hang and Ting, Kai Ming and Zhu, Ye},
  journal={Artificial Intelligence},
  pages={104440},
  year={2025},
  publisher={Elsevier}
}