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eclat1
- 关联规则程序1 This implementation is based on the Eclat algorithm (cfr. Zaki et al., 1997). Several optimizations have been added such as the use of diffsets. -an association rules procedures This implementation is based on th e Eclat algorithm (c
rules1
- 关联规则程序2 This implementation generates association rules, based on the Apriori algorithm (cfr. Agrawal et al.,1995). It takes as input a file of frequent sets in the format such as generated by the previous implementations. -association rules 2 Th
pairmining1
- 关联规则3 Rank-correlated set mining (Download) This implementation is based on the rank-correlated set mining technique for numerical attributes as described in the paper \"Mining rank-correlated sets of numerical attributes\" (Calders, Goethals, Ja
ndi1
- 关联规则4 NDI (Download) This implementation is based on the NDI algorithm (Calders and Goethals, 2002). Several optimizations have been added, such as a fast algorithm for the inclusion-exclusion (see Calders and Goethals, KDID 2005). The tar-ba
dic1
- 关联规则5 DIC (Download) This implementation is based on the Dynamic Itemset Counting (DIC) algorithm (cfr. Brin et al., 1997). The implementation contains no additional optimizations ans seems to perform worse than Apriori on almost all datasets I
fpgrowth
- This implementation generates association rules, based on the Apriori algorithm (cfr. Agrawal et al.,1995). It takes as input a file of frequent sets in the format such as generated by the previous implementations.
Data_Mining_SQL_2008
- 这是《数据挖掘原理与应用—SQL Server 2008数据库》的随书SQL语句、源代码和Excel范例文件,基于DMX,代码主要包括对SQL Server 2008和Excel 2007中已经集成好的数据挖掘算法的应用, 如贝叶斯聚类、决策树、时序、聚类、序列聚类、关联规则、神经网络、逻辑回归、OLAP立方体的等算法,具有极高的使用价值。-This is the " Principles and Applications of data mining-SQL Server 2008 d
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- 该算法主要实现了数据挖掘的关联规则Apriori算法-The algorithm achieved a major data mining Apriori algorithm for association rules
MSApriori
- Data mining purpose is to find interesting patterns within great number of data. One of its functionality is association that is finding association rule which meet minimum support value (minsup) and minimum confidence (minconf). Association techniqu
AR
- 数据挖掘关联规则算法APRIOR,高效的产生频繁相集-Data Mining Association Rules APRIOR, efficient set of the frequent phase