Comparative Study of Apriori and FP-Growth Algorithms using WEKA Tool
Nitisha Yadav
, Palak Baraiya , Nitika Goswami
Data mining, Association rule, Apriori, FP-Growth, WEKA
Manually analyzing pattern for frequently bought itemset is a cumbersome task. To solve this problem, many analytical data mining tools are available. Association rule mining is one of the data mining rule, which discovers interesting relation between variable from large dataset. Apriori & FP-Growth algorithm are the most common algorithm of association rule mining. This paper present the comparision of Apriori and FP-Growth algorithm on the basis of their execution time and memory space on supermarket dataset using WEKA tool. And the comparative result shown that the execution time of FP-Growth algorithm is much faster than Apriori algorithm & comes to the conclusion that FP-Growth is better for analyzing data quickly.
"Comparative Study of Apriori and FP-Growth Algorithms using WEKA Tool", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.1, Issue 5, page no.826 - 830, May-2016, Available :https://ijsdr.org/papers/IJSDR1605149.pdf
Volume 1
Issue 5,
May-2016
Pages : 826 - 830
Paper Reg. ID: IJSDR_160453
Published Paper Id: IJSDR1605149
Downloads: 000347075
Research Area: Engineering
Country: Dewas, Madhya Pradesh, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
