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IHPreten: A novel supervised learning framework with attribute regularization for prediction of incompatible herb pair in traditional Chinese medicine.

Jiajing ZhuYongguo LiuYun ZhangZhi ChenQiaoqin LiShangming YangXiaofeng LiuShuangqing ZhaiYi ZhangChuanbiao Wen
Published in: Neurocomputing (2019)
Keyphrases
  • traditional chinese medicine
  • supervised learning
  • training data
  • probabilistic model
  • decision trees
  • pairwise
  • knowledge acquisition