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nonordfp: An FP-growth variation without rebuilding the FP-tree

Balázs Rácz
2004 Workshop on Frequent Itemset Mining Implementations  
The theoretical difference is the main data structure (tree), which is more compact and which we do not need to rebuild for each conditional step.  ...  We thoroughly deal with implementation issues, data structures, memory layout, I/O and library functions we use to achieve comparable performance as the best implementations of the 1 st Frequent Itemset  ...  From the many published algorithms for this task, pattern growth approaches (FP-growth and its variations) were among the best performing ones.  ... 
dblp:conf/fimi/Racz04 fatcat:hn5c7yddyzdsjg6ln5lznrxpnu

Survey on the Techniques of FP-Growth Tree for Efficient Frequent Item-set Mining

Rana Krupali, Dweepna Garg
2017 International Journal of Computer Applications  
A Frequent pattern tree (FP-tree) is type of prefix tree that allows the detection of recurrent (frequent) item set exclusive of the candidate item set generation.  ...  In such situation FP is the best choice but problem with this approach is that it generates redundant FP Tree.  ...  FP-GROWTH TREE VARIATIONS 2.1 DynFP-Growth Algorithm [12] [13] [31] The Dyn FP-Growth has mainly focused to improve the FP-Tree algorithm construction based on the issues such as:  The resultant  ... 
doi:10.5120/ijca2017912958 fatcat:jmzutttz5vhznlnxoxvblckgc4

Survey or Analysis of Centralized and Distributed Association Rule Mining Algorithm

Viral Jethava, Risha Pandey
unpublished
The performance study shows that the fp-growth method is more efficient and scalable, is about an order of magnitude faster than the Apriori algorithm.  ...  This paper presents the comparison of the performances of Apriori, Frequent Pattern Growth and DIC algorithm.  ...  FP Tree algorithm is used to find the frequent itemset without the candidate itemset generation.  ... 
fatcat:kgswitflknfl5ckna37ptjt2l4