Other packages > Find by keyword >

RKEEL  

Using 'KEEL' in R Code
View on CRAN: Click here


Download and install RKEEL package within the R console
Install from CRAN:
install.packages("RKEEL")

Install from Github:
library("remotes")
install_github("cran/RKEEL")

Install by package version:
library("remotes")
install_version("RKEEL", "1.3.4")



Attach the package and use:
library("RKEEL")
Maintained by
Jose M. Moyano
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-01-31
Latest Update: 2023-09-14
Description:
'KEEL' is a popular 'Java' software for a large number of different knowledge data discovery tasks. This package takes the advantages of 'KEEL' and R, allowing to use 'KEEL' algorithms in simple R code. The implemented R code layer between R and 'KEEL' makes easy both using 'KEEL' algorithms in R as implementing new algorithms for 'RKEEL' in a very simple way. It includes more than 100 algorithms for classification, regression, preprocess, association rules and imbalance learning, which allows a more complete experimentation process. For more information about 'KEEL', see .
How to cite:
Jose M. Moyano (2016). RKEEL: Using 'KEEL' in R Code. R package version 1.3.4, https://cran.r-project.org/web/packages/RKEEL. Accessed 06 Aug. 2026.
Previous versions and publish date:
(2026-07-09 08:19), 1.1.5 (2016-01-31 16:36), 1.1.6 (2016-02-02 12:46), 1.1.15 (2017-01-11 08:59), 1.1.17 (2017-01-17 13:28), 1.1.18 (2017-01-18 18:07), 1.1.19 (2017-01-26 12:08), 1.1.20 (2017-01-31 09:10), 1.1.21 (2017-02-02 11:44), 1.1.22 (2017-08-10 17:13), 1.2.1 (2018-07-06 13:30), 1.2.2 (2018-07-16 20:40), 1.2.3 (2018-09-25 10:40), 1.2.5 (2018-12-19 21:30), 1.2.7 (2019-01-18 11:40), 1.3.1 (2019-07-18 13:40), 1.3.2 (2020-03-19 10:20), 1.3.3 (2021-05-13 16:12), 1.3.4 (2023-09-14 20:50)
Other packages that cited RKEEL R package
View RKEEL citation profile
Other R packages that RKEEL depends, imports, suggests or enhances
Complete documentation for RKEEL
Functions, R codes and Examples using the RKEEL R package
Some associated functions: ABB-IEP-FS . ANR-F . ART-C . AdaBoost-I . AdaBoostNC-C . Alatasetal-A . Alcalaetal-A . AllKNN-TSS . AllPosible-MV . Apriori-A . AssociationRulesAlgorithm . AssociativeClassificationAlgorithm . BNGE-C . BSE-C . Bayesian-D . Bojarczuk_GP-C . C45-C . C45Rules-C . C45_Binarization-C . CART-C . CART-R . CBA-C . CFAR-C . CFKNN-C . CHC-C . CMAR-C . CNN-C . CPAR-C . CPW-C . CW-C . C_SVM-C . CamNN-C . CenterNN-C . ClassificationAlgorithm . ClassificationResults . CleanAttributes-TR . ClusterAnalysis-D . DSM-C . DT_GA-C . DecimalScaling-TR . Decr-RBFN-C . Deeps-C . EARMGA-A . EPSILON_SVR-R . Eclat-A . FCRA-C . FPgrowth-A . FRNN-C . FRSBM-R . FURIA-C . Falco_GP-C . FuzzyApriori-A . FuzzyFARCHD-C . FuzzyKNN-C . FuzzyNPC-C . GANN-C . GAR-A . GENAR-A . GFS-AdaBoost-C . GFS-GP-R . GFS-GSP-R . GFS-LogitBoost-C . GFS-RB-MF-R . GeneticFuzzyApriori-A . GeneticFuzzyAprioriDC-A . ID3-C . ID3-D . IF_KNN-C . Ignore-MV . ImbalancedClassificationAlgorithm . Incr-RBFN-C . IterativePartitioningFilter-F . JFKNN-C . KMeans-MV . KNN-C . KNN-MV . KSNN-C . KStar-C . KeelAlgorithm . Kernel-C . LDA-C . LVF-IEP-FS . LinearLMS-C . LinearLMS-R . Logistic-C . M5-R . M5Rules-R . MLP-BP-C . MLP-BP-R . MODENAR-A . MOEA_Ghosh-A . MOPNAR-A . MinMax-TR . ModelCS-TSS . MostCommon-MV . NB-C . NICGAR-A . NM-C . NNEP-C . NU_SVM-C . NU_SVR-R . Nominal2Binary-TR . PART-C . PDFC-C . PFKNN-C . PNN-C . POP-TSS . PRISM-C . PSO_ACO-C . PSRCG-TSS . PUBLIC-C . PW-C . PolQuadraticLMS-C . PolQuadraticLMS-R . PreprocessAlgorithm . Proportional-D . QAR_CIP_NSGAII-A . QDA-C . RBFN-C . RBFN-R . RISE-C . RegressionAlgorithm . RegressionResults . Relief-FS . Ripper-C . SFS-IEP-FS . SGA-C . SMO-C . SSGA-Integer-knn-FS . SaturationFilter-F . Shrink-C . Slipper-C . Tan_GP-C . Thrift-R . UniformFrequency-D . UniformWidth-D . VWFuzzyKNN-C . WM-R . ZScore-TR . getAttributeLinesFromDataframes . hasContinuousData . hasMissingValues . isMultiClass . loadKeelDataset . readKeel . runCV . runParallel . runSequential . writeDatFromDataframe . writeDatFromDataframes . 
Some associated R codes: ABB-IEP-FS.R . ANR-F.R . ART-C.R . AdaBoost-I.R . AdaBoostNC-C.R . Alatasetal-A.R . Alcalaetal-A.R . AllKNN-TSS.R . AllPosible-MV.R . Apriori-A.R . AssociationRulesAlgorithm.R . AssociativeClassificationAlgorithm.R . BNGE-C.R . BSE-C.R . Bayesian-D.R . Bojarczuk_GP-C.R . C45-C.R . C45Rules-C.R . C45_Binarization-C.R . CART-C.R . CART-R.R . CBA-C.R . CFAR-C.R . CFKNN-C.R . CHC-C.R . CMAR-C.R . CNN-C.R . CPAR-C.R . CPW-C.R . CW-C.R . C_SVM-C.R . CamNN-C.R . CenterNN-C.R . ClassificationAlgorithm.R . ClassificationResults.R . CleanAttributes-TR.R . ClusterAnalysis-D.R . DSM-C.R . DT_GA-C.R . DecimalScaling-TR.R . Decr-RBFN-C.R . Deeps-C.R . EARMGA-A.R . EPSILON_SVR-R.R . Eclat-A.R . FCRA-C.R . FPgrowth-A.R . FRNN-C.R . FRSBM-R.R . FURIA-C.R . Falco_GP-C.R . FuzzyApriori-A.R . FuzzyFARCHD-C.R . FuzzyKNN-C.R . FuzzyNPC-C.R . GANN-C.R . GAR-A.R . GENAR-A.R . GFS-AdaBoost-C.R . GFS-GP-R.R . GFS-GSP-R.R . GFS-LogitBoost-C.R . GFS-RB-MF-R.R . GeneticFuzzyApriori-A.R . GeneticFuzzyAprioriDC-A.R . ID3-C.R . ID3-D.R . IF_KNN-C.R . Ignore-MV.R . ImbalancedClassificationAlgorithm.R . Incr-RBFN-C.R . IterativePartitioningFilter-F.R . JFKNN-C.R . KMeans-MV.R . KNN-C.R . KNN-MV.R . KSNN-C.R . KStar-C.R . KeelAlgorithm.R . KeelUtils.R . Kernel-C.R . LDA-C.R . LVF-IEP-FS.R . LinearLMS-C.R . LinearLMS-R.R . Logistic-C.R . M5-R.R . M5Rules-R.R . MLP-BP-C.R . MLP-BP-R.R . MODENAR-A.R . MOEA_Ghosh-A.R . MOPNAR-A.R . MinMax-TR.R . ModelCS-TSS.R . MostCommon-MV.R . NB-C.R . NICGAR-A.R . NM-C.R . NNEP-C.R . NU_SVM-C.R . NU_SVR-R.R . Nominal2Binary-TR.R . PART-C.R . PDFC-C.R . PFKNN-C.R . PNN-C.R . POP-TSS.R . PRISM-C.R . PSO_ACO-C.R . PSRCG-TSS.R . PUBLIC-C.R . PW-C.R . PolQuadraticLMS-C.R . PolQuadraticLMS-R.R . PreprocessAlgorithm.R . Proportional-D.R . QAR_CIP_NSGAII-A.R . QDA-C.R . RBFN-C.R . RBFN-R.R . RISE-C.R . RegressionAlgorithm.R . RegressionResults.R . Relief-FS.R . Ripper-C.R . SFS-IEP-FS.R . SGA-C.R . SMO-C.R . SSGA-Integer-knn-FS.R . SaturationFilter-F.R . Shrink-C.R . Slipper-C.R . Tan_GP-C.R . Thrift-R.R . UniformFrequency-D.R . UniformWidth-D.R . VWFuzzyKNN-C.R . WM-R.R . ZScore-TR.R .  Full RKEEL package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

SAMBA  
Selection and Misclassification Bias Adjustment for Logistic Regression Models
Health research using data from electronic health records (EHR) has gained popularity, but miscla ...
Download / Learn more Package Citations See dependency  
RRedshiftSQL  
R Interface to the 'Redshift' Database
Superclasses 'PostgreSQL' connection to help enable full 'dplyr' functionality on 'Redshift'. ...
Download / Learn more Package Citations See dependency  
lsmeans  
Least-Squares Means
Obtain least-squares means for linear, generalized linear, and mixed models. Compute contrasts or l ...
Download / Learn more Package Citations See dependency  
TMDb  
Access to TMDb API
Provides an R-interface to the TMDb API (see TMDb API on < ...
Download / Learn more Package Citations See dependency  
r2resize  
In-Text Resize for Images, Tables and Fancy Resize Containers in 'shiny', 'rmarkdown' and 'quarto' Documents
Automatic resizing toolbar for containers, images and tables. Various resizable or expandable contai ...
Download / Learn more Package Citations See dependency  

28,083

R Packages

239,283

Dependencies

74,457

Author Associations

28,084

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA