数理医药学杂志
數理醫藥學雜誌
수리의약학잡지
JOURNAL OF MATHEMATICAL MEDICINE
2013年
5期
550-551,552
,共3页
数据挖掘%中医诊断模型%分类算法
數據挖掘%中醫診斷模型%分類算法
수거알굴%중의진단모형%분류산법
data mining%diagnosis model of traditional Chinese medicine%classification algorithm
决策树和神经网络是经典的数据挖掘分类技术,介绍这两种常用分类技术及其在中医诊断模型构建中的应用,分析总结了算法的优势与不足,以期为研究者在选择算法时提供依据。
決策樹和神經網絡是經典的數據挖掘分類技術,介紹這兩種常用分類技術及其在中醫診斷模型構建中的應用,分析總結瞭算法的優勢與不足,以期為研究者在選擇算法時提供依據。
결책수화신경망락시경전적수거알굴분류기술,개소저량충상용분류기술급기재중의진단모형구건중적응용,분석총결료산법적우세여불족,이기위연구자재선택산법시제공의거。
The creation of diagnosis model of traditional Chinese medicine is the classification of tradi-tional Chinese medicine samples in essence .Classification decision tree and neural network are two classical data mining technologies .These two classification technologies and their application in the creation of diag-nosis model of traditional Chinese medicine are introduced in this paper .T he advantages and disadvantages of both technologies are analyzed in detail ,providing a basis for researchers to choose the appropriate algo-rithm .