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arules-A computational environment for mining association rules and frequent item sets
Mining frequent itemsets and association rules is a popular and well researched approach
for discovering interesting relationships between variables in large databases. The R …
for discovering interesting relationships between variables in large databases. The R …
Instance spaces for machine learning classification
This paper tackles the issue of objective performance evaluation of machine learning
classifiers, and the impact of the choice of test instances. Given that statistical properties or …
classifiers, and the impact of the choice of test instances. Given that statistical properties or …
An optimized FP-growth algorithm for discovery of association rules
Association rule mining (ARM) is a data mining technique to discover interesting
associations between datasets. The frequent pattern-growth (FP-growth) is an effective ARM …
associations between datasets. The frequent pattern-growth (FP-growth) is an effective ARM …
Data sanitization in association rule mining: An analytical review
A Telikani, A Shahbahrami - Expert Systems with Applications, 2018 - Elsevier
Association rule hiding is the process of transforming a transaction database into a sanitized
version to protect sensitive knowledge and patterns. The challenge is to minimize the side …
version to protect sensitive knowledge and patterns. The challenge is to minimize the side …
Itemset mining: A constraint programming perspective
The field of data mining has become accustomed to specifying constraints on patterns of
interest. A large number of systems and techniques has been developed for solving such …
interest. A large number of systems and techniques has been developed for solving such …
Fast and memory efficient mining of frequent closed itemsets
This paper presents a new scalable algorithm for discovering closed frequent itemsets, a
lossless and condensed representation of all the frequent itemsets that can be mined from a …
lossless and condensed representation of all the frequent itemsets that can be mined from a …
Genmax: An efficient algorithm for mining maximal frequent itemsets
We present GenMax, a backtrack search based algorithm for mining maximal frequent
itemsets. GenMax uses a number of optimizations to prune the search space. It uses a novel …
itemsets. GenMax uses a number of optimizations to prune the search space. It uses a novel …
[PDF][PDF] Introduction to arules–mining association rules and frequent item sets
Mining frequent itemsets and association rules is a popular and well researched approach
for discovering interesting relationships between variables in large databases. The R …
for discovering interesting relationships between variables in large databases. The R …
Constraint programming for itemset mining
The relationship between constraint-based mining and constraint programming is explored
by showing how the typical constraints used in pattern mining can be formulated for use in …
by showing how the typical constraints used in pattern mining can be formulated for use in …
A systematic approach to the assessment of fuzzy association rules
In order to allow for the analysis of data sets including numerical attributes, several
generalizations of association rule mining based on fuzzy sets have been proposed in the …
generalizations of association rule mining based on fuzzy sets have been proposed in the …