資源簡介
使用matlab實現apriori算法 包括頻繁項集的生成 和 關聯規則的發現

代碼片段和文件信息
function?[Fresupport]=apriori(dataSetminSupport)
%根據最小支持度minSupport在dataSet中選擇滿足條件的頻繁項集以及對于的支持度
Fre=[];
support=[];
%1、得到初始候選集
C1=initD(dataSet);
%2、過濾
[L1supportRate]=scanD(dataSetC1minSupport);
%3、得到第二輪的組合
Fre=[Fre;L1];
support=[support?supportRate];
combineFre=aprioriGen(L1);
flag=1;
while?flag>0
????%判斷是否進行到了最后
????[comRcomC]=size(combineFre);
????if?comR==1
????????flag=0;
????end
????[LsupportRate]=scanD(dataSetcombineFreminSupport);
????if?length(L)==0
????????flag=0;
????????continue;
????end
????Fre=[Fre;L];
????support=[support?supportRate];
????combineFre=aprioriGen(L);
end
?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????文件????????687??2015-05-13?21:03??apriori\apriori.m
?????文件????????278??2015-05-13?19:48??apriori\aprioriGen.m
?????文件????????649??2015-05-13?22:05??apriori\calRuler.m
?????文件????????263??2015-05-13?18:36??apriori\calSupport.m
?????文件????????186??2015-05-13?18:29??apriori\data.mat
?????文件????????178??2015-05-13?21:25??apriori\findVecIndexInMat.m
?????文件????????346??2015-05-13?18:15??apriori\initD.m
?????文件????????260??2015-05-14?09:19??apriori\main.m
?????文件????????475??2015-05-13?18:40??apriori\scanD.m
?????文件????????758??2015-05-14?09:37??apriori\splitVec.m
?????文件????????470??2015-05-13?19:47??apriori\uniqueCombineFre.m
?????目錄??????????0??2015-05-14?09:41??apriori
-----------?---------??----------?-----??----
?????????????????4550????????????????????12
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