title: Feature representation in the biclustering of symptom-herb relationship in Chinese medicine.
abstract: OBJECTIVE
  To find an appropriate feature representation in the biclustering of symptom-herb relationship in Chinese medicine (CM).
  
  
  METHODS
  Four different representation schemes were tested in identifying the complex relationship between symptoms and herbs using a biclustering algorithm on an insomnia data set. These representation schemes were effective count, binary value, relative success ratio, or modified relative success ratio. The comparison of the schemes was made on the number and size of biclusters with respect to different threshold values.
  
  
  CONCLUSIONS
  The modified relative success ratio scheme was the most appropriate feature representation among the four tested. Some of the biclusters selected from this representation scheme were known to follow the therapeutic principles of CM, while others may offer clues for further clinical investigations.
authors: School of Information Technologies, University of Sydney, Australia. josiah.poon@sydney.edu.au
authors: Josiah
authors: J
authors: Poon
authors: Zhe
authors: Z
authors: Luo
authors: Run-shun
authors: RS
authors: Zhang
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D004365:Drugs, Chinese Herbal / Q000627:therapeutic use*; D006801:Humans; D008516:Medicine, Chinese Traditional; D007319:Sleep Initiation and Maintenance Disorders / Q000188:drug therapy*
chemical_list: D004365:Drugs, Chinese Herbal