README.txt

0. This is the source code of the paper "A New Index for Clustering Evaluation Based on Density Estimation."

1. In function index_plot_first_n_label_one_data, if the index's score is "smaller is better", then the "smaller_better" hyper-parameter should be set to True. Otherwise, if the index's score is "larger is better", then the "smaller_better" hyper-parameter should be set to False.

2. Readers can test their own index function, the API is:
   
    def index_function(X, label):
   
    some codes to compute the index value ...
    
    return the_index_value

then call the index_plot_first_n_label_one_data function. Note the "smaller_better" hyper-parameter.

3. License.
   
License of the source code : Apache License, Version 2.0
License of new data: Creative Commons Attribution 4.0 International

4. Citation:

@article{liu2022new,
  title={A new index for clustering evaluation based on density estimation},
  author={Liu, Gangli},
  journal={arXiv preprint arXiv:2207.01294},
  year={2022}
}

5. The "multiple_label_145.p" file is larger than 100MB, so it is stored on Git Large File Storage (LFS), readers may need to download it separately.

6. Performance of other indices like Silhouette coefficient (SC), Calinski Harabasz index (CH) etc., can be found at:
https://github.com/mike-liuliu/Min-Max-Jump-distance/tree/main