| chkMLInterfaceProc |
MLInterfaces infrastructure |
| claraB |
An interface to various unsupervised machine learning methods for ExpressionSets |
| claraB,ExpressionSet,numeric-method |
An interface to various unsupervised machine learning methods for ExpressionSets |
| classbagg-class |
Class "classifOutput": container for output of classification procedures in R |
| classifOutput |
Class "classifOutput": container for output of classification procedures in R |
| classifOutput-class |
Class "classifOutput": container for output of classification procedures in R |
| clustOutput-class |
Class "clustOutput" container for cluster analysis results |
| cmeansB |
An interface to various unsupervised machine learning methods for ExpressionSets |
| cmeansB,ExpressionSet,numeric-method |
An interface to various unsupervised machine learning methods for ExpressionSets |
| confuMat |
Methods for Function confuMat in Package `MLInterfaces' |
| confuMat,classifOutput-method |
Methods for Function confuMat in Package `MLInterfaces' |
| confuMat-methods |
Methods for Function confuMat in Package `MLInterfaces' |
| confuMatTrain |
Methods for Function MLearn in Package `MLInterfaces' |
| confuMatTrain,classifOutput-method |
Methods for Function MLearn in Package `MLInterfaces' |
| cshell-class |
Class "classifOutput": container for output of classification procedures in R |
| cshellB |
An interface to various unsupervised machine learning methods for ExpressionSets |
| cshellB,ExpressionSet,numeric-method |
An interface to various unsupervised machine learning methods for ExpressionSets |
| cvB |
An interface to various machine learning methods for ExpressionSets |
| cvB,ExpressionSet,character-method |
An interface to various machine learning methods for ExpressionSets |
| kmeans-class |
Class "classifOutput": container for output of classification procedures in R |
| kmeansB |
An interface to various unsupervised machine learning methods for ExpressionSets |
| kmeansB,ExpressionSet,numeric-method |
An interface to various unsupervised machine learning methods for ExpressionSets |
| knn1B |
An interface to various machine learning methods for ExpressionSets |
| knn1B,ExpressionSet,character,integer-method |
An interface to various machine learning methods for ExpressionSets |
| knnB |
An interface to various machine learning methods for ExpressionSets |
| knnB,ExpressionSet,character,integer-method |
An interface to various machine learning methods for ExpressionSets |
| knnP |
An interface to various machine learning methods for ExpressionSets |
| knnP-class |
Class "classifOutput": container for output of classification procedures in R |
| last.warning |
An interface to various machine learning methods for ExpressionSets |
| lca-class |
Class "classifOutput": container for output of classification procedures in R |
| lcaB |
An interface to various machine learning methods for ExpressionSets |
| lcaB,ExpressionSet,numeric-method |
An interface to various machine learning methods for ExpressionSets |
| lda-class |
Class "classifOutput": container for output of classification procedures in R |
| ldaB |
An interface to various machine learning methods for ExpressionSets |
| ldaB,ExpressionSet,character,integer-method |
An interface to various machine learning methods for ExpressionSets |
| logitboost-class |
Class "classifOutput": container for output of classification procedures in R |
| logitboostB |
An interface to various machine learning methods for ExpressionSets |
| logitboostB,ExpressionSet,character,integer,numeric-method |
An interface to various machine learning methods for ExpressionSets |
| lvq1B |
An interface to various machine learning methods for ExpressionSets |
| lvq1B,ExpressionSet,character,integer-method |
An interface to various machine learning methods for ExpressionSets |
| lvq2B |
An interface to various machine learning methods for ExpressionSets |
| lvq2B,ExpressionSet,character,integer-method |
An interface to various machine learning methods for ExpressionSets |
| lvq3B |
An interface to various machine learning methods for ExpressionSets |
| lvq3B,ExpressionSet,character,integer-method |
An interface to various machine learning methods for ExpressionSets |
| makeCVFunc |
MLInterfaces infrastructure |
| membMat-class |
Class "classifOutput": container for output of classification procedures in R |
| mkfmla |
real adaboost (Friedman et al) (and discrete adaboost (DAB)) |
| MLearn |
Methods for Function MLearn in Package `MLInterfaces' |
| MLearn,formula,data.frame,character,numeric,ANY-method |
Methods for Function MLearn in Package `MLInterfaces' |
| MLearn,formula,data.frame,character,numeric-method |
Methods for Function MLearn in Package `MLInterfaces' |
| MLearn,formula,ExpressionSet,character,numeric,ANY-method |
Methods for Function MLearn in Package `MLInterfaces' |
| MLearn,formula,ExpressionSet,character,numeric-method |
Methods for Function MLearn in Package `MLInterfaces' |
| MLearn-methods |
Methods for Function MLearn in Package `MLInterfaces' |
| MLLabel |
Class "classifOutput": container for output of classification procedures in R |
| MLLabel-class |
Class "classifOutput": container for output of classification procedures in R |
| MLOutput |
Class "classifOutput": container for output of classification procedures in R |
| MLOutput-class |
Class "classifOutput": container for output of classification procedures in R |
| MLScore |
Class "classifOutput": container for output of classification procedures in R |
| MLScore-class |
Class "classifOutput": container for output of classification procedures in R |
| pam-class |
Class "classifOutput": container for output of classification procedures in R |
| pamB |
An interface to various unsupervised machine learning methods for ExpressionSets |
| pamB,ExpressionSet,numeric-method |
An interface to various unsupervised machine learning methods for ExpressionSets |
| pamr-class |
Class "classifOutput": container for output of classification procedures in R |
| pamrB |
An interface to various machine learning methods for ExpressionSets |
| pamrB,ExpressionSet,character,integer-method |
An interface to various machine learning methods for ExpressionSets |
| planarPlot |
Methods for Function planarPlot in Package `MLInterfaces' |
| planarPlot,classifOutput,data.frame,character-method |
Methods for Function planarPlot in Package `MLInterfaces' |
| planarPlot,classifOutput,ExpressionSet,character-method |
Methods for Function planarPlot in Package `MLInterfaces' |
| planarPlot-methods |
Methods for Function planarPlot in Package `MLInterfaces' |
| plot,varImpStruct,ANY-method |
Class "varImpStruct" - collect data on variable importance from various machine learning methods |
| plot,varImpStruct-method |
Class "varImpStruct" - collect data on variable importance from various machine learning methods |
| prcomp-class |
Class "classifOutput": container for output of classification procedures in R |
| predClass-class |
Class "classifOutput": container for output of classification procedures in R |
| Predict |
real adaboost (Friedman et al) (and discrete adaboost (DAB)) |
| Predict,daboostCont-method |
real adaboost (Friedman et al) (and discrete adaboost (DAB)) |
| Predict,raboostCont-method |
real adaboost (Friedman et al) (and discrete adaboost (DAB)) |
| predict.knnP |
MLInterfaces infrastructure |
| predLabels |
An interface to various machine learning methods for ExpressionSets |
| predLabels,classifOutput-method |
An interface to various machine learning methods for ExpressionSets |
| predLabels,MLOutput-method |
An interface to various machine learning methods for ExpressionSets |
| predLabelsTr |
Methods for Function MLearn in Package `MLInterfaces' |
| predLabelsTr,classifOutput-method |
Methods for Function MLearn in Package `MLInterfaces' |
| print.knnP |
MLInterfaces infrastructure |
| probArray-class |
Class "classifOutput": container for output of classification procedures in R |
| probMat-class |
Class "classifOutput": container for output of classification procedures in R |
| show,clustOutput-method |
Class "clustOutput" container for cluster analysis results |
| show,membMat-method |
An interface to various machine learning methods for ExpressionSets |
| show,MLOutput-method |
An interface to various machine learning methods for ExpressionSets |
| show,probArray-method |
An interface to various machine learning methods for ExpressionSets |
| show,probMat-method |
An interface to various machine learning methods for ExpressionSets |
| show,qualScore-method |
An interface to various machine learning methods for ExpressionSets |
| show,raboostCont-method |
Class "raboostCont" ~~~ |
| show,silhouetteVec-method |
An interface to various machine learning methods for ExpressionSets |
| show,SOMBout-method |
An interface to self-organizing map methods for ExpressionSets |
| show,somout-method |
An interface to self-organizing map methods for ExpressionSets |
| show,varImpStruct-method |
Class "varImpStruct" - collect data on variable importance from various machine learning methods |
| silhouetteB |
An interface to various unsupervised machine learning methods for ExpressionSets |
| silhouetteB,classifOutput-method |
Class "classifOutput": container for output of classification procedures in R |
| silhouetteB,clustOutput-method |
Class "clustOutput" container for cluster analysis results |
| silhouetteVec-class |
Class "classifOutput": container for output of classification procedures in R |
| slda-class |
Class "classifOutput": container for output of classification procedures in R |
| sldaB |
An interface to various machine learning methods for ExpressionSets |
| sldaB,ExpressionSet,character,integer-method |
An interface to various machine learning methods for ExpressionSets |
| SOMB |
An interface to self-organizing map methods for ExpressionSets |
| somB |
An interface to self-organizing map methods for ExpressionSets |
| SOMB,ExpressionSet,character-method |
An interface to self-organizing map methods for ExpressionSets |
| somB,ExpressionSet,character-method |
An interface to self-organizing map methods for ExpressionSets |
| SOMBout-class |
Class "classifOutput": container for output of classification procedures in R |
| somout-class |
An interface to self-organizing map methods for ExpressionSets |
| stat.diag.daB |
An interface to various machine learning methods for ExpressionSets |
| stat.diag.daB,ExpressionSet,character,integer-method |
An interface to various machine learning methods for ExpressionSets |
| svm-class |
Class "classifOutput": container for output of classification procedures in R |
| svmB |
An interface to various machine learning methods for ExpressionSets |
| svmB,ExpressionSet,character,integer-method |
An interface to various machine learning methods for ExpressionSets |
| xval |
support for cross-validatory machine learning with ExpressionSets |
| xval,ExpressionSet,character,genericFunction,character,integer-method |
support for cross-validatory machine learning with ExpressionSets |
| xval,ExpressionSet,character,genericFunction,character,missing-method |
support for cross-validatory machine learning with ExpressionSets |
| xval,ExpressionSet,character,nonstandardGeneric,character,integer-method |
support for cross-validatory machine learning with ExpressionSets |
| xval,ExpressionSet,character,nonstandardGeneric,character,missing-method |
support for cross-validatory machine learning with ExpressionSets |
| xval-methods |
support for cross-validatory machine learning with ExpressionSets |
| xvalLoop |
Cross-validation in clustered computing environments |
| xvalLoop,ANY-method |
Cross-validation in clustered computing environments |
| xvalLoop-methods |
Cross-validation in clustered computing environments |
| xvalML |
support for cross-validatory machine learning with ExpressionSets |
| xvalML,formula,ExpressionSet,character,character,missing,missing,missing,function,missing,missing,missing-method |
support for cross-validatory machine learning with ExpressionSets |
| xvalML,formula,ExpressionSet,character,character,missing,missing,missing,function,numeric,missing,missing-method |
support for cross-validatory machine learning with ExpressionSets |
| xvalML,formula,ExpressionSet,character,character,missing,missing,missing,missing,missing,missing,missing-method |
support for cross-validatory machine learning with ExpressionSets |
| xvalML,formula,ExpressionSet,character,character,missing,missing,missing,missing,missing,missing-method |
support for cross-validatory machine learning with ExpressionSets |
| xvalML,formula,ExpressionSet,character,character,missing-method |
support for cross-validatory machine learning with ExpressionSets |
| xvalML,formula,ExpressionSet,character,character,numeric,ANY,ANY,ANY,ANY,ANY,ANY-method |
support for cross-validatory machine learning with ExpressionSets |
| xvalML,formula,ExpressionSet,character,character,numeric,ANY,ANY,ANY,ANY,ANY-method |
support for cross-validatory machine learning with ExpressionSets |
| xvalML,formula,ExpressionSet,character,character,numeric-method |
support for cross-validatory machine learning with ExpressionSets |