What is it about?
The study created a model for an enhanced FP-Growth algorithm by inserting a second pruning process after the FP tree has been constructed. The enhanced algorithm will examine the resulting tree to further eliminate the items that are less significant and less interesting based on a given condition.
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Why is it important?
As some generated patterns have weak items, the solution produced by the enhanced FP-Growth algorithm creates interesting patterns. The model can be used with different datasets for pattern generation like weblogs, preferences, and similar purposes.
Perspectives
To further strengthen the frequent pattern generation, this study creates a version of the FP-Growth method.
Roseclaremath Caroro
Misamis University
Read the Original
This page is a summary of: An Enhanced Frequent Pattern-Growth Algorithm with Dual Pruning using Modified Anti-Monotone Support, November 2018, Institute of Electrical & Electronics Engineers (IEEE),
DOI: 10.1109/hnicem.2018.8666366.
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