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SDR (version 0.7.0.0)

Subgroup Discovery Algorithms for R

Description

Implementation of some algorithms for the data mining task called "subgroup discovery" without package dependencies. It also provide a Shiny App for make the analysis easier. The algorithms works with data sets provided in KEEL or ARFF format files or data.frame objects. If you want more information about KEEL format, please refer to < http://www.keel.es > .

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Version

Install

install.packages('SDR')

Monthly Downloads

10

Version

0.7.0.0

License

LGPL (>= 3) | file LICENSE

Issues

0

Pull Requests

0

Stars

3

Forks

4

Maintainer

Angel M Garcia

Last Published

January 16th, 2016

Functions in SDR (0.7.0.0)

Pop.evaluate

Evaluates the entire population for the Global Fitness computation procedure.
SDR_GUI

Launch a web interface for use the algorithms easily.
FuGePSD_crossover

Performs the FuGePSD crossover function.
createNewRule

Creates a random general rule
NMEEF_SD

Non-dominated Multi-objective Evolutionary algorithm for Extracting Fuzzy rules in Subgroup Discovery (NMEEF-SD)
summary.keel

S3 function to summary a keel object
Pop.fuzzyReasoningMethod

Calcultes the Fuzzy Reasoning Method for all examples for a given rule population
tournamentSelection

Performs tournament selection for the FuGePSD algorithm
Rule.evaluate

Evaluate a single rule.
print.keel

S3 function to print in console the contents of the dataset
modifyFuzzyCrispIntervals

Modifiy the number of Fuzzy Labels of the dataset.
Rule.addVariable

Add a new random variable to the antecedent of the rule.
Rule.exchangeVariables

Create a new rule by mixing the antecedent part of two rules.
parseTime

Parse a time differente to "x hours, y minutes and z seconds"
Rule.clearAntecedent

Remove completely the antecedent part of a rule.
Rule.compatibility

Return the compatibility degrees of a rule with all instances of a given dataset.
read.keel

Reads a KEEL data format file or an ARFF data format file.
habermanTst

Haberman survival data set
carTra

Car evaluation dataset
keelFromDataFrame

Creates a keel object from a data.frame
Rule.changeLabel

Change randomly a label associated to the rule with a non-existing label on the rule
MESDIF

Multiobjective Evolutionary Subgroup DIscovery Fuzzy rules (MESDIF) Algorithm
tokenCompetition

Runs a token competition procedure.
Rule.toCANVectorRepresentation

Converts a rule antecedent to a CANONICA vector representation
writeRuleFile

Writes rules into a human-readable format into a file.
germanTst

German Credit data set
germanTra

German Credit data set
SDR

SDR: A package for Subgroup Discovery algorithms in R
changeTargetVariable

Change the target Variable of a 'keel' Dataset
SDIGA

Subgroup Discovery Iterative Genetic Algorithm (SDIGA)
save.keel

Saves a keel dataset into a KEEL dataset format file.
FUGEPSD

Fuzzy Genetic Programming-based learning for Subgroup Discovery (FuGePSD) Algorithm.
Rule.addLabel

Adds a new random label to the variable selected in the rule.
improvedTable

Improved table creation for .get_values6
habermanTra

Haberman survival data set
Rule.deleteVariable

Delete a random variable from a rule
addKeelRegister

Add one or a set of instances to a KEEL dataset.
keelFromARFF

Reads an ARFF file
FuGePSD_Mutation

Perfom the mutation operator for FuGePSD algorithm.
carTst

Car evaluation dataset
printFuGePSDParameters

Prints parameters information aboute the execution of the algorithm in console and in the output file specified by this parameters.
writeTestQMFile

Writes rules into a human-readable format into a file.