A Novel Reduction Method Based On Attributes Similarity In Chinese Traditional Medicine Prescriptions

According to the similarity among data attributes, this paper proposes a reduction method of high dimensional data. Different from the existed algorithms, this method takes attributes as basic vectors in high dimensions space, and data tuples as vector sum of attributes vectors. With the transcendental concept similar information between attributes, the weight computing is defined as formulas of attribute vectors and their projects on each other, and the final result is gotten from three simplifying algorithms which are proposed in this paper. The paper analyzes the new method, and compares reduced results between different algorithms. This method is successfully applied in automatic induction of Chinese traditional medicine prescription. The extension experiments prove the validity of the method.