Effectively Interpreting Electroencephalogram Classification Using the Shapley Sampling Value to Prune a Feature Tree

Kazuki Tachikawa, Yuji Kawai, JiHoon Park, Minoru Asada. Effectively Interpreting Electroencephalogram Classification Using the Shapley Sampling Value to Prune a Feature Tree. In Vera Kurková, Yannis Manolopoulos, Barbara Hammer, Lazaros S. Iliadis, Ilias Maglogiannis, editors, Artificial Neural Networks and Machine Learning - ICANN 2018 - 27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, Proceedings, Part III. Volume 11141 of Lecture Notes in Computer Science, pages 672-681, Springer, 2018. [doi]

@inproceedings{TachikawaKPA18,
  title = {Effectively Interpreting Electroencephalogram Classification Using the Shapley Sampling Value to Prune a Feature Tree},
  author = {Kazuki Tachikawa and Yuji Kawai and JiHoon Park and Minoru Asada},
  year = {2018},
  doi = {10.1007/978-3-030-01424-7_66},
  url = {https://doi.org/10.1007/978-3-030-01424-7_66},
  researchr = {https://researchr.org/publication/TachikawaKPA18},
  cites = {0},
  citedby = {0},
  pages = {672-681},
  booktitle = {Artificial Neural Networks and Machine Learning - ICANN 2018 - 27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, Proceedings, Part III},
  editor = {Vera Kurková and Yannis Manolopoulos and Barbara Hammer and Lazaros S. Iliadis and Ilias Maglogiannis},
  volume = {11141},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-030-01424-7},
}