This paper investigates a brute-force technique for mining classification rules from large data sets. We employ an association rule miner enhanced with new pruning strategies to c...
The single minimum support (minsup) based frequent pattern mining approaches like Apriori and FP-growth suffer from“rare item problem”while extracting frequent patterns. That...
Mining association rules may generate a large numbers of rules making the results hard to analyze manually. Pasquier et al. have discussed the generation of GuiguesDuquenne–Luxe...
Frequent patterns provide solutions to datasets that do not have well-structured feature vectors. However, frequent pattern mining is non-trivial since the number of unique patter...
Wei Fan, Kun Zhang, Hong Cheng, Jing Gao, Xifeng Y...
Data on individuals and entities are being collected widely. These data can contain information that explicitly identifies the individual (e.g., social security number). Data can ...