NDLI: Particle swarm optimization based fuzzy frequent pattern mining from gene expression data

Content Provider	IEEE Xplore Digital Library
Author	Mishra, S. Mishra, D. Satapathy, S.K.
Copyright Year	2011
Description	Author affiliation: Institute of Technical Education & Research, Siksha O Anusandhan University, Bhubaneswar, Odisha, India (Mishra, S.; Mishra, D.; Satapathy, S.K.)
Abstract	The FP-growth algorithm is currently one of the fastest approaches to frequent item set mining. Fuzzy logic provides a mathematical framework where the entire range of the data lies in between 0 and 1. The PSO algorithm was developed from observations of the social behavior of animals, including bird flocking and fish schooling. It is easier to implement than evolutionary algorithms because it only involves a single operator for updating solutions. In contrast, evolutionary algorithms require a particular representation and specific methods for cross-over, mutation, and selection. Furthermore, PSO has been found to be very effective in a wide variety of applications, being able to produce good solutions at a very low computational cost. In this paper, we have considered the fuzzified dataset and have implemented various frequent pattern mining techniques. Out of the various frequent pattern mining techniques it was found that Frequent Pattern (FP) growth method yields us better results on a fuzzy dataset. Here, the frequent patterns obtained are considered as the set of initial population. For the selection criteria, we had considered the mean squared residue score rather using the threshold value. It was observed that out of the four fuzzy based frequent mining techniques, the PSO based fuzzy FP growth technique finds the best individual frequent patterns. Also, the run time of the algorithm and the number of frequent patterns generated is far better than the rest of the techniques used.
Starting Page	15
Ending Page	20
File Size	187357
Page Count	6
File Format	PDF
ISBN	9781457713859
e-ISBN	9781457713866
DOI	10.1109/ICCCT.2011.6075204
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-15
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Fuzzy logic FP growth tree Databases Clustering algorithms Frequent pattern mining Apriori algorithm Classification algorithms Data mining Particle swarm optimization Vertical data format
Content Type	Text
Resource Type	Article

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