数据挖掘在线测试.docx

一个食品连锁店每周的事务记录如下表所示，其中每一条事务表示在一项收款机业务中卖出的项目，假定supmin=20%，confmin=40%，使用Apriori算法计算生成的关联规则，标明每趟数据库扫描时的候选集和大项目集。?事务项目事务项目? ??T1??? T2?????????????????????? T3面包、果冻、花生酱面包、花生酱面包、牛奶、花生酱??? T4??? T5啤酒、面包啤酒、牛奶?解：（1）由I={面包、果冻、花生酱、牛奶、啤酒}的所有项目直接产生1-候选C1，计算其支持度，取出支持度大于supmin的项集，形成1-频繁集L1，如下表所示：?项集C1 支持度项集L1支持度{面包} {花生酱} {牛奶} {啤酒} 4/53/52/52/5{面包} {花生酱} {牛奶} {啤酒} 4/5 3/5 2/5 2/5(2)组合连接L1中的各项目，产生2-候选集C2，计算其支持度，取出支持度小于supmin的项集，形成2-频繁集L2，如下表所示：项集C2支持度项集L2支持度{面包、花生酱} 3/5{面包、花生酱} 3/5至此，所有频繁集都被找到，算法结束，所以，confidence（{面包}→{花生酱}）=（4/5）/（3/5）=4/3 confmin confidence（{ 花生酱}→{面包}）=（3/5）/（4/5）=3/4 confmin所以，关联规则{面包}→{花生酱}、{ 花生酱}→{面包}均是强关联规则。The following shows a history of customers with their incomes, ages and an attribute called “Have_iPhone”indicating whether they have an iPhone. We also indicate whether they will buy an iPad or not in the lastcolumn.No.?? Income????? Age??? ?Have_iPhone?? Buy_iPad1??????? high??????? young?????? yes?????????????? yes2??????? high?????? ?old???????????yes?????????????? yes3??????? medium?? young?????? no??????????????? yes4??????? high????? ? old??????????? no??????????????? yes5??????? medium?? young?????? no?????????????? ?no6??????? medium?? young?????? no??????????????? no7??????? medium?? old?????????? no????????????????no8??????? medium?? old?????????? no??????????????? no(a) We want to train a CART decision tree classifier to predict whether a new customer will buy an iPad or not. We define the value of attribute Buy_iPad is the label of a record.(i) Please find a CART decision tree according to the above example. In the decision tree, wheneverwe process a node containing at most 3 records, we stop to process this node for splitting.(ii) Consider a new young customer whose income is medium and he has an iPhone. Please predictwhether this new custom