Mining Frequent Pattern by Titanic and FP-Tree algorithms

Authors

  • Youssef FAKIR  Laboratory of Information Processing and Decision Support, Faculty of Sciences and Technics, Sultan Moulay Slimane Unversity, Morocco
  • Rachid El AYACHI  Laboratory of Information Processing and Decision Support, Faculty of Sciences and Technics, Sultan Moulay Slimane Unversity, Morocco
  • Mohamed FAKIR  

DOI:

https://doi.org//10.32628/CSEIT206537

Keywords:

Data mining, Association rules, FP-Tree, TITANIC algorithm

Abstract

Extraction of itemset frequent is an important theme in Datamining. Several algorithm have been developed based on Apriori algorithm during the last decades. This paper deals with the FP- tree and Titanic algorithms. FP-Tree is an improvement to the Apriori method witch generate frequents itemsets without generating candidate. The Titanic algorithm traverses the level search space by focusing on the determination of the minimum generators (or key Item sets). In addition, this paper studies the differences between these two algorithms and shows advantages and disadvantages of each one.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2020-10-30

Issue

Volume 6, Issue 5, September-October-2020

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Youssef FAKIR, Rachid El AYACHI, Mohamed FAKIR, " Mining Frequent Pattern by Titanic and FP-Tree algorithms, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 6, Issue 5, pp.208-215, September-October-2020. Available at doi : https://doi.org/10.32628/CSEIT206537