Package: nuggets 1.5.0

nuggets: Extensible Data Pattern Searching Framework

Extensible framework for subgroup discovery (Atzmueller (2015) <doi:10.1002/widm.1144>), contrast patterns (Chen (2022) <doi:10.48550/arXiv.2209.13556>), emerging patterns (Dong (1999) <doi:10.1145/312129.312191>), association rules (Agrawal (1994) <https://www.vldb.org/conf/1994/P487.PDF>) and conditional correlations (Hájek (1978) <doi:10.1007/978-3-642-66943-9>). Both crisp (Boolean, binary) and fuzzy data are supported. It generates conditions in the form of elementary conjunctions, evaluates them on a dataset and checks the induced sub-data for interesting statistical properties. A user-defined function may be defined to evaluate on each generated condition to search for custom patterns.

Authors:Michal Burda [aut, cre]

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nuggets/json (API)
NEWS

# Install 'nuggets' in R:
install.packages('nuggets', repos = c('https://beerda.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/beerda/nuggets/issues

Pkgdown site:https://beerda.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

association-rule-miningcontrast-pattern-miningdata-miningfuzzyknowledge-discoverypattern-recognitioncppopenmp

5.38 score 2 stars 10 scripts 296 downloads 23 exports 41 dependencies

Last updated 19 days agofrom:1e0e6421b6. Checks:8 OK, 4 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 13 2025
R-4.5-win-x86_64NOTEMar 13 2025
R-4.5-mac-x86_64NOTEMar 13 2025
R-4.5-mac-aarch64NOTEMar 13 2025
R-4.5-linux-x86_64NOTEMar 13 2025
R-4.4-win-x86_64OKMar 13 2025
R-4.4-mac-x86_64OKMar 13 2025
R-4.4-mac-aarch64OKMar 13 2025
R-4.4-linux-x86_64OKMar 13 2025
R-4.3-win-x86_64OKMar 13 2025
R-4.3-mac-x86_64OKMar 13 2025
R-4.3-mac-aarch64OKMar 13 2025

Exports:dichotomizedigdig_associationsdig_baseline_contrastsdig_complement_contrastsdig_contrastsdig_correlationsdig_griddig_implicationsdig_paired_baseline_contrastsfireformat_conditionis_almost_constantis_conditionis_degreeis_subsetparse_conditionpartitionremove_almost_constantremove_ill_conditionsvar_gridvar_nameswhich_antichain

Dependencies:briocallrclicpp11crayondescdiffobjdigestdplyrevaluatefansifastmatchfsgenericsgluejsonlitelifecyclemagrittrpillarpkgbuildpkgconfigpkgloadpraiseprocessxpspurrrR6RcppRcppThreadrlangrprojrootstringistringrtestthattibbletidyrtidyselectutf8vctrswaldowithr

nuggets: Get Started

Rendered fromnuggets.Rmdusingknitr::rmarkdownon Mar 13 2025.

Last update: 2024-12-17
Started: 2024-11-16

Readme and manuals

Help Manual

Help pageTopics
Search for patterns of custom typedig
Search for association rulesdig_associations
Search for conditions that yield in statistically significant one-sample test in selected variables.dig_baseline_contrasts
Search for conditions that provide significant differences in selected variables to the rest of the data tabledig_complement_contrasts
Search for conditional correlationsdig_correlations
Search for grid-based rulesdig_grid
Search for conditions that provide significant differences between paired variablesdig_paired_baseline_contrasts
Obtain truth-degrees of conditionsfire
Format a vector of predicates into a string with a conditionformat_condition
Tests if almost all values in a vector are the same.is_almost_constant
Check whether the given list of character vectors contains a list of valid conditions.is_condition
Tests whether the given argument is a numeric value from the interval [0,1]is_degree
Determine whether the first vector is a subset of the second vectoris_subset
Convert character vector of conditions into a list of vectors of predicatesparse_condition
Convert columns of data frame to Boolean or fuzzy sets (of triangular, trapezoidal, or raised-cosinal shape)partition
Remove almost constant columns from a data frameremove_almost_constant
From a given list remove those elements that are not valid conditions.remove_ill_conditions
Create a tibble of combinations of selected column namesvar_grid
Extract variable names from predicatesvar_names
Return indices of first elements of the list, which are incomparable with preceding elements.which_antichain