Accordingly, this work presents a new FP-tree structure (NFP-tree) and develops an efficient approach for mining frequent itemsets, based on an NFP-tree, called�...
Against the above shortcomings, we propose an FP-tree-based algorithm MMFI optimized with array and matrix for mining the maximal frequent itemsets. It not only�...
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In this paper, a new algorithm named APFT is proposed, it combines the Apriori algorithm and FP-tree structure which proposed in FP-growth algorithm. The�...
We present a new algorithm for mining maximal frequent itemsets from a transactional database. The search strategy of the algorithm integrates a depth-first�...
NFP-tree employs two counters in a tree node to reduce the number of tree nodes. Additionally, the header table of the NFP-tree is smaller than that of the FP-�...
The original FPGrowth algorithm takes as input a threshold named "minsup" and a transaction database. A frequent itemset is an itemset having a support higher�...
Mar 20, 2024 � The FP-Growth Algorithm offers an efficient approach for discovering frequent item sets in data mining tasks, bypassing the need for generating candidate sets�...
DMFIA algorithm based on FP-Tree accesses database only twice, produces maximum frequent itemsets by non-conditional pattern and non-conditional FP-Tree, but.
Jun 11, 2023 � The FP Growth algorithm in data mining is a popular method for frequent pattern mining. The algorithm is efficient for mining frequent item sets in large�...
May 18, 2022 � The research introduces an FP-MFIA algorithm that can efficiently mine the maximum frequent itemsets to deal with long-pattern frequent itemset excavation.