Package: RKEEL 1.3.4
RKEEL: Using 'KEEL' in R Code
'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/>.
Authors:
RKEEL_1.3.4.tar.gz
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RKEEL_1.3.4.tgz(r-4.4-any)RKEEL_1.3.4.tgz(r-4.3-any)
RKEEL_1.3.4.tar.gz(r-4.5-noble)RKEEL_1.3.4.tar.gz(r-4.4-noble)
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RKEEL.pdf |RKEEL.html✨
RKEEL/json (API)
# Install 'RKEEL' in R: |
install.packages('RKEEL', repos = c('https://i02momuj.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 1 years agofrom:2aaf54ca2b. Checks:OK: 1 WARNING: 1 NOTE: 5. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 11 2024 |
R-4.5-win | NOTE | Nov 11 2024 |
R-4.5-linux | WARNING | Nov 11 2024 |
R-4.4-win | NOTE | Nov 11 2024 |
R-4.4-mac | NOTE | Nov 11 2024 |
R-4.3-win | NOTE | Nov 11 2024 |
R-4.3-mac | NOTE | Nov 11 2024 |
Exports:ABB_IEP_FSAdaBoost_IAdaBoostNC_CAlatasetal_AAlcalaetal_AAllKNN_TSSAllPosible_MVANR_FApriori_AART_CAssociationRulesAlgorithmAssociativeClassificationAlgorithmBayesian_DBNGE_CBojarczuk_GP_CBSE_CC_SVM_CC45_CC45Binarization_CC45Rules_CCamNN_CCART_CCART_RCBA_CCenterNN_CCFAR_CCFKNN_CCHC_CClassificationAlgorithmClassificationResultsCleanAttributes_TRClusterAnalysis_DCMAR_CCNN_CCPAR_CCPW_CCW_CDecimalScaling_TRDecrRBFN_CDeeps_CdownloadFromMirrorDSM_CDT_GA_CEARMGA_AEclat_AEPSILON_SVR_RFalco_GP_CFCRA_CFPgrowth_AFRNN_CFRSBM_RFURIA_CFuzzyApriori_AFuzzyFARCHD_CFuzzyKNN_CFuzzyNPC_CGANN_CGAR_AGENAR_AGeneticFuzzyApriori_AGeneticFuzzyAprioriDC_AgetAttributeLinesFromDataframesgetExePathgetJarListgetJarPathGFS_AdaBoost_CGFS_GP_RGFS_GSP_RGFS_LogitBoost_CGFS_RB_MF_RhasContinuousDatahasMissingValuesID3_CID3_DIF_KNN_CIgnore_MVImbalancedClassificationAlgorithmIncrRBFN_CisMultiClassIterativePartitioningFilter_FJFKNN_CKeelAlgorithmKernel_CKMeans_MVKNN_CKNN_MVKSNN_CKStar_CLDA_CLinearLMS_CLinearLMS_RloadKeelDatasetLogistic_CLVF_IEP_FSM5_RM5Rules_RMinMax_TRMLP_BP_CMLP_BP_RModelCS_TSSMODENAR_AMOEA_Ghosh_AMOPNAR_AMostCommon_MVNB_CNICGAR_ANM_CNNEP_CNominal2Binary_TRNU_SVM_CNU_SVR_RPART_CPDFC_CPFKNN_CPNN_CPolQuadraticLMS_CPolQuadraticLMS_RPOP_TSSPreprocessAlgorithmPRISM_CProportional_DPSO_ACO_CPSRCG_TSSPUBLIC_CPW_CQAR_CIP_NSGAII_AQDA_CR6_ABB_IEP_FSR6_AdaBoost_IR6_AdaBoostNC_CR6_Alatasetal_AR6_Alcalaetal_AR6_AllKNN_TSSR6_AllPosible_MVR6_ANR_FR6_Apriori_AR6_ART_CR6_Bayesian_DR6_BNGE_CR6_Bojarczuk_GP_CR6_BSE_CR6_C_SVM_CR6_C45_CR6_C45Binarization_CR6_C45Rules_CR6_CamNN_CR6_CART_CR6_CART_RR6_CBA_CR6_CenterNN_CR6_CFAR_CR6_CFKNN_CR6_CHC_CR6_CleanAttributes_TRR6_ClusterAnalysis_DR6_CMAR_CR6_CNN_CR6_CPAR_CR6_CPW_CR6_CW_CR6_DecimalScaling_TRR6_DecrRBFN_CR6_Deeps_CR6_DSM_CR6_DT_GA_CR6_EARMGA_AR6_Eclat_AR6_EPSILON_SVR_RR6_Falco_GP_CR6_FCRA_CR6_FPgrowth_AR6_FRNN_CR6_FRSBM_RR6_FURIA_CR6_FuzzyApriori_AR6_FuzzyFARCHD_CR6_FuzzyKNN_CR6_FuzzyNPC_CR6_GANN_CR6_GAR_AR6_GENAR_AR6_GeneticFuzzyApriori_AR6_GeneticFuzzyAprioriDC_AR6_GFS_AdaBoost_CR6_GFS_GP_RR6_GFS_GSP_RR6_GFS_LogitBoost_CR6_GFS_RB_MF_RR6_ID3_CR6_ID3_DR6_IF_KNN_CR6_Ignore_MVR6_IncrRBFN_CR6_IterativePartitioningFilter_FR6_JFKNN_CR6_Kernel_CR6_KMeans_MVR6_KNN_CR6_KNN_MVR6_KSNN_CR6_KStar_CR6_LDA_CR6_LinearLMS_CR6_LinearLMS_RR6_Logistic_CR6_LVF_IEP_FSR6_M5_RR6_M5Rules_RR6_MinMax_TRR6_MLP_BP_CR6_MLP_BP_RR6_ModelCS_TSSR6_MODENAR_AR6_MOEA_Ghosh_AR6_MOPNAR_AR6_MostCommon_MVR6_NB_CR6_NICGAR_AR6_NM_CR6_NNEP_CR6_Nominal2Binary_TRR6_NU_SVM_CR6_NU_SVR_RR6_PART_CR6_PDFC_CR6_PFKNN_CR6_PNN_CR6_PolQuadraticLMS_CR6_PolQuadraticLMS_RR6_POP_TSSR6_PRISM_CR6_Proportional_DR6_PSO_ACO_CR6_PSRCG_TSSR6_PUBLIC_CR6_PW_CR6_QAR_CIP_NSGAII_AR6_QDA_CR6_RBFN_CR6_RBFN_RR6_Relief_FSR6_Ripper_CR6_RISE_CR6_SaturationFilter_FR6_SFS_IEP_FSR6_SGA_CR6_Shrink_CR6_Slipper_CR6_SMO_CR6_SSGA_Integer_knn_FSR6_Tan_GP_CR6_Thrift_RR6_UniformFrequency_DR6_UniformWidth_DR6_VWFuzzyKNN_CR6_WM_RR6_ZScore_TRRBFN_CRBFN_Rread.keelRegressionAlgorithmRegressionResultsRelief_FSRipper_CRISE_CrunCVrunParallelrunSequentialSaturationFilter_FSFS_IEP_FSSGA_CShrink_CSlipper_CSMO_CSSGA_Integer_knn_FSTan_GP_CThrift_RUniformFrequency_DUniformWidth_DVWFuzzyKNN_CWM_RwriteDatFromDataframewriteDatFromDataframesZScore_TR
Dependencies:arulesaskpassclicodetoolsdigestdoParalleldownloaderforeachgdatagenericsgluegtoolsiteratorslatticelifecyclemagrittrMatrixopensslpmmlR6rJavaRKEELdatarlangstringistringrsysvctrsXML