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: 2023-08-19
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 <http://www.keel.es/>.
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
Previous versions and publish date:
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)
Other packages that cited RKEEL R package
View RKEEL citation profile
Other R packages that RKEEL depends, imports, suggests or enhances
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
Get rewarded with contribution points by helping add
Reviews / comments / questions /suggestions ↴↴↴

Today's Hot Picks in Authors and Packages

Deriv  
Symbolic Differentiation
R-based solution for symbolic differentiation. It admits user-defined function as well as function s ...
Download / Learn more Package Citations See dependency  
nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
lgarch  
Simulation and Estimation of Log-GARCH Models
Simulation and estimation of univariate and multivariate log-GARCH models. The main functions of the ...
Download / Learn more Package Citations See dependency  
bulletr  
Algorithms for Matching Bullet Lands
Analyze bullet lands using nonparametric methods. We provide a reading routine for x3p files (see &l ...
Download / Learn more Package Citations See dependency  
buildr  
Organize & Run Build Scripts Comfortably
Working with reproducible reports or any other similar projects often require to run the script that ...
Download / Learn more Package Citations See dependency  

22,086

R Packages

187,731

Dependencies

55,244

Author Associations

22,087

Publication Badges

© Copyright 2022 - present. All right reserved, rpkg.net. Contact Us / Suggestions / Concerns