Application Research On New Attribute Reduction Algorithm To Spleen And Stomach Syndrome Differentiation

Rough set theory is a knowledge analysis theory which can process vague, uncertain and inconsistent data. One of the most important objects of study in rough set theory is attribute reduction, and it has been applied to pattern recognition, decision analysis, data mining and medical system areas.This paper applies the data that offered by Spleen Institute in Guangzhou University of Chinese Medicine. The goal is to find the relevant attribute information which can differentiate the spleen deficiency syndrome and spleen-stomach dampness-heat syndrome by the new attribute reduction method. The raw data may be incomplete and inaccurate, and even is redundant because the chronic gastritis mechanism is not clear, while the rough set is just a powerful tool to process this kind of knowledge.This paper improves the attribute reduction algorithm by rewriting the attribute significance which brings in the expert knowledge in the basis of not changing the ability of rough set classification. It is entirely different from the methods of traditional medical statistics and fuzzy comprehensive evaluation method. The rough set theory not remains on the surface of data and it can be used to dig up the depth information in the data set. During the experiment, we reduce the attributes by using the new attribute reduction algorithm, and we then reduce the value and extract the rules on the new decision list, and the last step is classification prediction and its accurate achieves 92.6%. We design and implement diagnostic system for rough set theory spleen deficiency syndrome differentiation. The experiment results show that this method is effective and feasible.