Showing 8 of total 8 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 1 months ago.
arulesassociation-rulesfrequent-itemsets
67.3 match 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
10.5 match 54 stars 11.00 score 1.7k scripts 2 dependents
malaga-fca-group
fcaR:Formal Concept Analysis
Provides tools to perform fuzzy formal concept analysis, presented in Wille (1982) <doi:10.1007/978-3-642-01815-2_23> and in Ganter and Obiedkov (2016) <doi:10.1007/978-3-662-49291-8>. It provides functions to load and save a formal context, extract its concept lattice and implications. In addition, one can use the implications to compute semantic closures of fuzzy sets and, thus, build recommendation systems.
Maintained by Domingo Lopez Rodriguez. Last updated 2 years ago.
3.3 match 6 stars 6.02 score 70 scripts
cumulocity-iot
pmml:Generate PMML for Various Models
The Predictive Model Markup Language (PMML) is an XML-based language which provides a way for applications to define machine learning, statistical and data mining models and to share models between PMML compliant applications. More information about the PMML industry standard and the Data Mining Group can be found at <http://dmg.org/>. The generated PMML can be imported into any PMML consuming application, such as Zementis Predictive Analytics products. The package isofor (used for anomaly detection) can be installed with devtools::install_github("gravesee/isofor").
Maintained by Dmitriy Bolotov. Last updated 3 years ago.
1.7 match 20 stars 7.98 score 560 scripts 1 dependents
jaroslav-kuchar
rCBA:CBA Classifier for R
Provides implementations of a classifier based on the "Classification Based on Associations" (CBA). It can be used for building classification models from association rules. Rules are pruned in the order of precedence given by the sort criteria and a default rule is added. The final classifier labels provided instances. CBA was originally proposed by Liu, B. Hsu, W. and Ma, Y. Integrating Classification and Association Rule Mining. Proceedings KDD-98, New York, 27-31 August. AAAI. pp80-86 (1998, ISBN:1-57735-070-7).
Maintained by Jaroslav Kuchar. Last updated 6 years ago.
1.8 match 7 stars 4.14 score 39 scripts
kliegr
arc:Association Rule Classification
Implements the Classification-based on Association Rules (CBA) algorithm for association rule classification. The package, also described in Hahsler et al. (2019) <doi:10.32614/RJ-2019-048>, contains several convenience methods that allow to automatically set CBA parameters (minimum confidence, minimum support) and it also natively handles numeric attributes by integrating a pre-discretization step. The rule generation phase is handled by the 'arules' package. To further decrease the size of the CBA models produced by the 'arc' package, postprocessing by the 'qCBA' package is suggested.
Maintained by Tomas Kliegr. Last updated 6 months ago.
0.5 match 7 stars 5.09 score 39 scripts 1 dependents
nikolett0203
RulesTools:Preparing, Analyzing, and Visualizing Association Rules
Streamlines data preprocessing, analysis, and visualization for association rule mining. Designed to work with the 'arules' package, features include discretizing data frames, generating rule set intersections, and visualizing rules with heatmaps and Euler diagrams. 'RulesTools' also includes a dataset on Brook trout detection from Nolan et al. (2022) <doi:10.1007/s13412-022-00800-x>.
Maintained by Nikolett Toth. Last updated 2 months ago.
0.5 match 3.93 score
cran
arulesSequences:Mining Frequent Sequences
Add-on for arules to handle and mine frequent sequences. Provides interfaces to the C++ implementation of cSPADE by Mohammed J. Zaki.
Maintained by Christian Buchta. Last updated 7 months ago.
0.5 match 12 stars 3.67 score 107 scripts