Application Of Decision Trees For Different Periods Of Ischemic Stroke Syndromes Variation

The rapid development in the field of Chinese Medicine syndrome diagosis system ofApoplexy, and sensor technology is continually upgrading the conflict between the power tosupply all kind of data and the ability to analyze them. To relax this situation, data miningtechnologycameontothestage.As one of the theoryof Data Mining, Decision Tree is a simple mathematical model thatis established by using computer and correlative statistical software. It is a reliable andeffective decision making technique that provide high classification accuracy with a simplerepresentationofgatheredknowledge.In chinese medical decision-making there are many situations where decision must bemadeeffectivelyandreliably. Conceptual simple decisionmakingmodels withthepossibilityof automatic learning are the most appropriate for performing such tasks. By providing abetter clue for analyzing complicated chinese medical data, it has been applyingin researchesof chinese medicine syndrome, such as diagnosis, classification, prediction and clinicalexperience summary. Making a good use of decision tree could overcome some defects oftraditionalstatisticalmethods.In order to study and to improve the the prediction accuracy of chinese medicinesyndrome of ischemic apoplexy, the paper made contributions in three aspects: first, usingrelatedconclusionsofdecisiontreetheorytoanalyzeandmodifychinesemedicinesyndrome;then, supplementing association analysis, another theory of Data Mining, to help enhance thegeneralization performance of decision tree algorithms; finally, evaluating above works inpractice.The paper present the basic characteristics of decision trees and the successful alliancewith the association analysis approach with the emphasis on existing and possible futureapplicationsinchinesemedicinesyndromeofischemicapoplexy.With the deeper application of decision tree, it is to exhibit important application valuesandbroaddevelopingprospectsinthefieldofChineseMedicinesyndromediagosissystemofapoplexy.