Paper_IJPE_Repository_2_Data_of_Generated_Rules_by_FP-Growth_10000
Published: 16 March 2025| Version 2 | DOI: 10.17632/g2c9g5prv3.2
Contributor:
SAMIA GAMOURADescription
We used RapidMiner V10.2 to design a process using the FP-Growth algorithm having the input of 10,000 augmented purchaces (see https://data.mendeley.com/drafts/24j2xp2xvy) . Running this process has generated 56 association-rules that are available in this data table.
Files
Steps to reproduce
We used RapidMiner V10.2 to design a process using the FP-Growth algorithm with specific parameter settings (minimum Support threshold = 0.6, minimum items per itemset = 1, maximum number of itemsets = 3, minimum Confidence = 0.1). The process comprises four main blocks : (Input) ==> Data Retrieve ==> Set Role ==> FP-Growth ==> Create Association Rules - (Output)
Institutions
EM Strasbourg Business School
Categories
Unsupervised Learning, Association Rule Learning