The cluster effect and clustering performance of spectral clustering are improved by using the particle center to construct the spectral clustering similarity matrix.

These program mainly containing:

• a synthetic dataset and real dataset folder named "dataset".
• four python files

• Pycharm
• Windows operating system
• scipy==1.8.1
• matplotlib ==3.5.2
• numpy==1.23.1
• psutil ==5.9.1
• scikit-learn==1.1.1
• sklearn==0.0
• pandas==1.4.3
• seaborn==0.11.2

• The synthetic dataset is not labeled, and the format is csv. You need to call GranularBallSynthetic to generate a granular-ball.
• The format of the real dataset is mat. You need to call GranularBallUCI to generate a granular-ball.

Run GranularBallSyntheticSC.py to obtain the results of the granular-ball based spectral clustering algorithm on the synthetic dataset, and run GranularBallUCISC.py to obtain the results of the granular-ballbased spectral clustering algorithm on the real dataset.