Data-driven Feature Selection for Long Longitudinal Breadth and High Dimensional Dataset: Empirical Studies of Metabolic Syndrome Prediction

Ji-Han Liu, Cheng-Tse Wu, Ta-Wei Chu, Jyh-Shing Roger Jang. Data-driven Feature Selection for Long Longitudinal Breadth and High Dimensional Dataset: Empirical Studies of Metabolic Syndrome Prediction. In ICMLC 2020: 2020 12th International Conference on Machine Learning and Computing, Shenzhen, China, February 15-17, 2020. pages 208-212, ACM, 2020. [doi]

@inproceedings{LiuWCJ20,
  title = {Data-driven Feature Selection for Long Longitudinal Breadth and High Dimensional Dataset: Empirical Studies of Metabolic Syndrome Prediction},
  author = {Ji-Han Liu and Cheng-Tse Wu and Ta-Wei Chu and Jyh-Shing Roger Jang},
  year = {2020},
  doi = {10.1145/3383972.3383992},
  url = {https://doi.org/10.1145/3383972.3383992},
  researchr = {https://researchr.org/publication/LiuWCJ20},
  cites = {0},
  citedby = {0},
  pages = {208-212},
  booktitle = {ICMLC 2020: 2020 12th International Conference on Machine Learning and Computing, Shenzhen, China, February 15-17, 2020},
  publisher = {ACM},
  isbn = {978-1-4503-7642-6},
}