A Novel Model for Predicting Dengue Disease using Enhanced Weighted FP-Growth
DOI:
https://doi.org/10.26438/ijcse/v7i1.655658Keywords:
Data Mining, Association rule mining, Fp-growth algorithmrithm, Apriori algorithmrithmAbstract
FP-Growth algorithm requirements to construct an FP-tree which contains all the datasets. Association rules mining is an imperative technology within DM. FP-Growth algorithm is a conventional algorithm in association rules mining. But the FP-Growth algorithm within mining wants two times to examine database, which reduce the effectiveness of algorithm. During the study of association rules mining with FP-Growth algorithm, we work out enhanced algorithm of FP-Growth algorithm—Painting-Growth algorithm. We compare weighted FP-Growth algorithm with Painting-Growth algorithm. Experimental results explain that Painting-Growth algorithm is faster than the biased FP-Growth algorithm. The presentation of the Painting-Growth algorithm is improved than to of FP-Growth algorithm.
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