Classification and Discrimination for Traditional Chinese Medicine Nature Based on OSC-OPLS/O2PLS-DA

The research for Chinese herbs´ warm and cold natures classification is a significative thing for clinical. The paper put forward a new model classification and discrimination for Traditional Chinese medicine(TCM)´ nature based on orthogonal signal correction-orthogonal partial least squares-discriminant analysis (OSC-OPLS/O2PLS-DA) after normalization. The first, data preprocessing and normalization for the metabolites sample space´s data, and the results data 135 multiply 839 dimension consist of three sections: warm nature´s normalization sample, cold nature´s normalization sample, blank group normalization sample; The second, OSC, dimension reduction and noise reduction for the metabolites sample space´s data; the third, OPLS/O2PLS-DA, Generate classification and discrimination Method for Traditional Chinese medicine(TCM)´ nature. The model was proved to be feasible and effective after tested with 6 type´s warm nature´s herbs, 6 type´s cold nature´s herbs.