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>.

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>.

Add-on for arules to handle and mine frequent sequences.
    Provides interfaces to the C++ implementation of cSPADE by  
    Mohammed J. Zaki.

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>.

Parse Autonomous Recording Unit (ARU) data and for sub-sampling recordings. 
    Extract Metadata from your recordings, select a subset of recordings for 
    interpretation, and prepare files for processing on the 
    'WildTrax' <https://wildtrax.ca/> platform. Read and process metadata 
    from recordings collected using the SongMeter and BAR-LT types of ARUs.

An interface to the API for 'arXiv',
    a repository of electronic preprints for
    computer science, mathematics, physics, quantitative biology,
    quantitative finance, and statistics.

Data sets are referred to in the text "Applied Survival Analysis Using R"
 by Dirk F. Moore, Springer, 2016, ISBN: 978-3-319-31243-9, <DOI:10.1007/978-3-319-31245-3>.

Contains functions from: Aho, K. (2014) Foundational and Applied Statistics for Biologists using R.  CRC/Taylor and Francis, Boca Raton, FL, ISBN: 978-1-4398-7338-0.

Datasets to be used primarily in conjunction with Ascent
    training materials but also for the book 'SAMS Teach Yourself R in 24 Hours' (ISBN: 978-0-672-33848-9).
    Version 1.0-7 is largely for use with the book; however, version 1.1 has a much greater focus on use with
    training materials, whilst retaining compatibility with the book.