Apriori算法的问题Apriori算法在做数据挖掘的时候只考虑某几种商品一次出现的情况,而没有考虑多次出现的情况.举

Uncertainty based on Weka data mining platform
Abstract:The traditional association rule mining algorithm Apriori algorithm is the basic principle and ideology,for the position has been accurately can only handle a given object,using the open source Weka platform,through the data conversion,processing uncertain data sets,on the iris data Testing Laboratory,digging out some useful results associated.

On the Apriori algorithm and its simulation in computer system
Abstract:The traditional Apriori algorithm for association rule mining large time overhead for the inadequacies of Apriori algorithm,based on relational algebra theory,and related operations using relational matrix is given frequent itemset search relational algebra-based theory of association rule mining (ORAR ) algorithm.Relationship matrix used to scan the database only once,in order to reduce the algorithm running time,mining frequent itemsets,and finally the simulation results comparing the two algorithms the execution time,discussed the data sample size and minimum support on algorithm performance.Through a large number of simulation experiments showed that the improvement of ORAR algorithm is efficient,reducing the frequent itemset mining dataset running time.

abc的支持数P1=3,acd的支持数P2=3,bcd的支持数P3=3,关联规则的输出就是在由频繁项集的项组成的关联规则中,找出置信度大于等于最小置信度阈值的关联规则.因为由频繁项集的项组成的关联规则的支持度大于等于最小支持阈...

To Apriori algorithm improvement and realization research
abstract:The traditional connection rule excavates the Apriori algorithm time expenses to be big,proposed excavates the ORAR algorithm based on the relational algebra theory connection rule,only must scan database one time using the relational matrix.Through the massive simulation experiment proved the improvement the ORAR algorithm is highly effective,reduced the excavation large number according to the centralism frequent item of collection running time.
Key word:Apriori; ORAR; Improvement; Relational matrix; Connection rule