A Novel Model for Predicting Dengue Disease using Enhanced Weighted FP-Growth - Upadhyay, Tanvi; Chaturvedi, Sushil (International Journal of Computer Sciences and Engineering, 2019)
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.