Showing 6 of total 6 results (show query)
mhahsler
arules:Mining Association Rules and Frequent Itemsets
Provides the infrastructure for representing, manipulating and analyzing transaction data and patterns (frequent itemsets and association rules). Also provides C implementations of the association mining algorithms Apriori and Eclat. Hahsler, Gruen and Hornik (2005) <doi:10.18637/jss.v014.i15>.
Maintained by Michael Hahsler. Last updated 2 months ago.
arulesassociation-rulesfrequent-itemsets
194 stars 13.99 score 3.3k scripts 28 dependentsmhahsler
arulesViz:Visualizing Association Rules and Frequent Itemsets
Extends package 'arules' with various visualization techniques for association rules and itemsets. The package also includes several interactive visualizations for rule exploration. Michael Hahsler (2017) <doi:10.32614/RJ-2017-047>.
Maintained by Michael Hahsler. Last updated 7 months ago.
arulesassociation-rulesfrequent-itemsetsinteractive-visualizationsvisualization
54 stars 11.03 score 1.7k scripts 2 dependentsmhahsler
arulesCBA:Classification Based on Association Rules
Provides the infrastructure for association rule-based classification including the algorithms CBA, CMAR, CPAR, C4.5, FOIL, PART, PRM, RCAR, and RIPPER to build associative classifiers. Hahsler et al (2019) <doi:10.32614/RJ-2019-048>.
Maintained by Michael Hahsler. Last updated 7 months ago.
association-rulesclassification
3 stars 5.42 score 47 scripts 1 dependents
beerda
lfl:Linguistic Fuzzy Logic
Various algorithms related to linguistic fuzzy logic: mining for linguistic fuzzy association rules, composition of fuzzy relations, performing perception-based logical deduction (PbLD), and forecasting time-series using fuzzy rule-based ensemble (FRBE). The package also contains basic fuzzy-related algebraic functions capable of handling missing values in different styles (Bochvar, Sobocinski, Kleene etc.), computation of Sugeno integrals and fuzzy transform.
Maintained by Michal Burda. Last updated 5 months ago.
association-rulesforecast-modelfuzzy-logicinference-rulescppopenmp
8 stars 5.35 score 28 scripts
firefly-cpp
niarules:Numerical Association Rule Mining using Population-Based Nature-Inspired Algorithms
Framework is devoted to mining numerical association rules through the utilization of nature-inspired algorithms for optimization. Drawing inspiration from the 'NiaARM' 'Python' and the 'NiaARM' 'Julia' packages, this repository introduces the capability to perform numerical association rule mining in the R programming language. Fister Jr., Iglesias, Galvez, Del Ser, Osaba and Fister (2018) <doi:10.1007/978-3-030-03493-1_9>.
Maintained by Iztok Jr. Fister. Last updated 24 days ago.
association-rulesmetaheuristicsoptimization
1 stars 3.70 score 2 scriptsmhahsler
arulesNBMiner:Mining NB-Frequent Itemsets and NB-Precise Rules
NBMiner is an implementation of the model-based mining algorithm for mining NB-frequent itemsets and NB-precise rules. Michael Hahsler (2006) <doi:10.1007/s10618-005-0026-2>.
Maintained by Michael Hahsler. Last updated 3 years ago.
6 stars 3.48 score 10 scripts