模式识别与人工智能
模式識彆與人工智能
모식식별여인공지능
Moshi Shibie yu Rengong Zhineng
2014年
1期
28-34
,共7页
关联规则%信息熵%频繁模式
關聯規則%信息熵%頻繁模式
관련규칙%신식적%빈번모식
Association Rule%Information Entropy%Frequent Pattern
关联规则挖掘时,数据集中各项目的重要性不同且较难主观给出,直接影响挖掘结果。针对此问题,给出加权项目集和加权关联规则的概念,并通过信息熵来确定单属性的权重,同时采用几何均值和取最大权重值的折中方法来确定多项目集的权重,以此在兼顾整体权重的同时,突出重要项目。在此基础上,采用加权频繁模式树来提取加权频繁模式,并给出加权频繁模式树的构造方法,最后以国家天文台提供的天体光谱数据及机械装备EDEM数据作为数据集,实验验证算法的高效率。
關聯規則挖掘時,數據集中各項目的重要性不同且較難主觀給齣,直接影響挖掘結果。針對此問題,給齣加權項目集和加權關聯規則的概唸,併通過信息熵來確定單屬性的權重,同時採用幾何均值和取最大權重值的摺中方法來確定多項目集的權重,以此在兼顧整體權重的同時,突齣重要項目。在此基礎上,採用加權頻繁模式樹來提取加權頻繁模式,併給齣加權頻繁模式樹的構造方法,最後以國傢天文檯提供的天體光譜數據及機械裝備EDEM數據作為數據集,實驗驗證算法的高效率。
관련규칙알굴시,수거집중각항목적중요성불동차교난주관급출,직접영향알굴결과。침대차문제,급출가권항목집화가권관련규칙적개념,병통과신식적래학정단속성적권중,동시채용궤하균치화취최대권중치적절중방법래학정다항목집적권중,이차재겸고정체권중적동시,돌출중요항목。재차기출상,채용가권빈번모식수래제취가권빈번모식,병급출가권빈번모식수적구조방법,최후이국가천문태제공적천체광보수거급궤계장비EDEM수거작위수거집,실험험증산법적고효솔。
In association rule mining, the importance of items is different and can not be subjectively given, which affects the mining result. The weighted items and weighted association rules are given, in which the weights of single attribute are determined by information entropy and the weights of items are determined by the compromise method between geometric mean and maximum weight value. Thus, the important projects are highlighted and the overall weights are balanced at the same time. On the basis of all above factors, weighted frequent patterns are extracted by using weighted frequent pattern tree, and the structure method of weighted frequent pattern tree is given. Finally, the experimental results on the spectral data of celestial body and the mechanical equipment EDEM verify the high efficiency of the proposed algorithm.