Subgroup Discovery with Evolutionary Fuzzy Systems in R

Implementation of evolutionary fuzzy systems for the data mining task called "subgroup discovery". It also provide a Shiny App for make the analysis easier. The algorithms works with data sets provided in KEEL, ARFF and CSV format and also with data.frame objects.


News

Changelog

Version 0.7.1.0

  • Change the name of the read.keel() function to read.dataset().
  • Added direct support for CSV files on read.dataset().
  • Rename keel class to SDEFSR_Dataset class.
  • Rename keelFromDataFrame() to SDEFSR_DatasetFromDataFrame().
  • Added a new object SDEFSR_Rules which:
    • Contains all rules generated by an SD algorithm an its associated quality measures.
    • The "[]" operator supports filter rules by quality measure
    • Added S3 method "sort" to sort rules by a given quality measure
  • Added new method plotRules() which shows a TPR vs FPR plot by using ggplot2 package.
  • Fixed error when reading ARFF files with quoted '' variables.
  • Changes of the UI:
    • Added a new visualization method: Variable vs variable
    • Added functionality to filter numerical variables
    • Added functionality to filter instences by the given numeric or categorical filters
    • On quality measure tab, the functionality to show the plot of plotRules() is displayed
    • Changed the server logic to work with the new SDEFSR_Rules object to improve performance on large results.

Version 0.7.0.0

  • Added a new subgroup discovery algorithm: FuGePSD.
  • New dataset files support:
    • ARFF files support from read.keel()
    • Conversion from data.frame to keel with keelFromDataFrame() function.
  • Minor optimizations when reading a file.
  • Some algorithm optimizations, changed a bit the way of calling the functions Be aware with this!
  • Fixed problem of the algorithms that returns four files instead of three. Now all the algorithms (except FuGePSD) returns three files.
  • Created S3 method to visualize keel objects with print() and summarize with summary()
  • Changes of the UI:
    • Algorithm selection an parameters now are on the tab panel of the right side of the UI after "Exploratory analysis". We think with this change the user has a better workflow and a better visualitation and organization of the results.
    • Also, the new functionality is available on the GUI, except the conversion from data.frame.

Reference manual

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install.packages("SDEFSR")

0.7.1.0 by Angel M. Garcia, a year ago


https://github.com/aklxao2/SDR


Browse source code at https://github.com/cran/SDEFSR


Authors: Angel M. Garcia [aut, cre], Pedro Gonzalez [aut, cph], Cristobal J. Carmona [aut, cph], Francisco Charte [ctb], Maria J. del Jesus [aut, cph]


Documentation:   PDF Manual  


LGPL (>= 3) | file LICENSE license


Imports grDevices, methods, parallel, stats, utils

Suggests ggplot2, knitr, shiny


See at CRAN