14 packages on CRAN
Implements clustering techniques such as Proximus and Rock, utility functions for efficient computation of cross distances and data manipulation.
Add-on for arules to handle and mine frequent sequences. Provides interfaces to the C++ implementation of cSPADE by Mohammed J. Zaki.
Data structures and algorithms for sparse arrays and matrices, based on index arrays and simple triplet representations, respectively.
Infrastructure for seriation with an implementation of several seriation/sequencing techniques to reorder matrices, dissimilarity matrices, and dendrograms. Also provides (optimally) reordered heatmaps, color images and clustering visualizations like dissimilarity plots, and visual assessment of cluster tendency plots (VAT and iVAT).
Provides an extensible framework for the efficient calculation of auto- and cross-proximities, along with implementations of the most popular ones.
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.
ISO language, territory, currency, script and character codes. Provides ISO 639 language codes, ISO 3166 territory codes, ISO 4217 currency codes, ISO 15924 script codes, and the ISO 8859 character codes as well as the UN M.49 area codes.
An R interface to Weka (Version 3.9.2). Weka is a collection of machine learning algorithms for data mining tasks written in Java, containing tools for data pre-processing, classification, regression, clustering, association rules, and visualization. Package 'RWeka' contains the interface code, the Weka jar is in a separate package 'RWekajars'. For more information on Weka see <http://www.cs.waikato.ac.nz/ml/weka/>.
Utilities for text analysis.
R interface to the GNU Linear Programming Kit. 'GLPK' is open source software for solving large-scale linear programming (LP), mixed integer linear programming ('MILP') and other related problems.
Data structures and basic operations for ordinary sets, generalizations such as fuzzy sets, multisets, and fuzzy multisets, customizable sets, and intervals.
Data structures and algorithms for k-ary relations with arbitrary domains, featuring relational algebra, predicate functions, and fitters for consensus relations.
Text categorization based on n-grams.
An abstract DList class helps storing large list-type objects in a distributed manner. Corresponding high-level functions and methods for handling distributed storage (DStorage) and lists allows for processing such DLists on distributed systems efficiently. In doing so it uses a well defined storage backend implemented based on the DStorage class.