MPC: A Novel Internal Clustering Validity Index Based on Midpoint-Involved Distance

Yating Zuo, Zhujuan Ma, Erzhou Zhu. MPC: A Novel Internal Clustering Validity Index Based on Midpoint-Involved Distance. In Zahir Tari, Keqiu Li, Hongyi Wu, editors, Algorithms and Architectures for Parallel Processing - 23rd International Conference, ICA3PP 2023, Tianjin, China, October 20-22, 2023, Proceedings, Part III. Volume 14489 of Lecture Notes in Computer Science, pages 310-323, Springer, 2023. [doi]

@inproceedings{ZuoMZ23,
  title = {MPC: A Novel Internal Clustering Validity Index Based on Midpoint-Involved Distance},
  author = {Yating Zuo and Zhujuan Ma and Erzhou Zhu},
  year = {2023},
  doi = {10.1007/978-981-97-0798-0_18},
  url = {https://doi.org/10.1007/978-981-97-0798-0_18},
  researchr = {https://researchr.org/publication/ZuoMZ23},
  cites = {0},
  citedby = {0},
  pages = {310-323},
  booktitle = {Algorithms and Architectures for Parallel Processing - 23rd International Conference, ICA3PP 2023, Tianjin, China, October 20-22, 2023, Proceedings, Part III},
  editor = {Zahir Tari and Keqiu Li and Hongyi Wu},
  volume = {14489},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-981-97-0798-0},
}