68 citations · 140 across the 7 of their papers we have counts for
7 papers
ARULESPY: Exploring Association Rules and Frequent Itemsets in Python
Michael Hahsler
The R arules package implements a comprehensive infrastructure for representing, manipulating, and analyzing transaction data and patterns using frequent itemsets and association r…
recommenderlab: An R Framework for Developing and Testing Recommendation Algorithms
Michael Hahsler
Algorithms that create recommendations based on observed data have significant commercial value for online retailers and many other industries. Recommender systems have a significa…
Swapped Face Detection using Deep Learning and Subjective Assessment
Xinyi Ding, Zohreh Raziei, Eric C. Larson +3
The tremendous success of deep learning for imaging applications has resulted in numerous beneficial advances. Unfortunately, this success has also been a catalyst for malicious us…
A Model-Based Frequency Constraint for Mining Associations from Transaction Data
Michael Hahsler
Mining frequent itemsets is a popular method for finding associated items in databases. For this method, support, the co-occurrence frequency of the items which form an association…
Optimizing Web Sites for Customer Retention
Michael Hahsler
With customer relationship management (CRM) companies move away from a mainly product-centered view to a customer-centered view. Resulting from this change, the effective managemen…
New probabilistic interest measures for association rules
Michael Hahsler, Kurt Hornik
Mining association rules is an important technique for discovering meaningful patterns in transaction databases. Many different measures of interestingness have been proposed for a…