Mining Weighted Frequent Patterns using ̳Weighted_FPGrowth’- A modified FP-Growth
نویسنده
چکیده
-------------------------------------------------------------------ABSTRACT--------------------------------------------------------------Mining Frequent Patterns is one of the primary step in Association Rule Mining (ARM). ARM always aims to produce relationships between different attributes of a database. Sometimes we may require including the weights (or significance) of different attributes in the ARM process; but such type of mining cannot be handled using traditional ARM approaches. To facilitate the concept of weighted attributes this paper has implemented the concept of Weighted Frequent Patterns by modifying the well known FP-growth algorithm. The modified algorithm is named as ‘Weighted_FPGrowth’. We know that some patterns are not frequent at all, but they may be significant enough in some cases. Theoretical analysis and experimental work have shown that the modified approach is able to
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