bagging-class |
Class "classifOutput": container for output of classification procedures in R |
baggingB |
An interface to various machine learning methods for ExpressionSets |
baggingB,ExpressionSet,character,integer-method |
An interface to various machine learning methods for ExpressionSets |
baggingI |
revised MLearn interface for machine learning |
balKfold |
support for cross-validatory machine learning with ExpressionSets |
balKfold.xvspec |
generate a partition function for cross-validation, where the partitions are approximately balanced with respect to the distribution of a response variable |
bclust-class |
Class "clustOutput" container for cluster analysis results |
bclustB |
An interface to various unsupervised machine learning methods for ExpressionSets |
bclustB,ExpressionSet,numeric-method |
An interface to various unsupervised machine learning methods for ExpressionSets |
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 |
classifierOutput-class |
Class "classifierOutput" |
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 |
Compute the confusion matrix for a classifier. |
confuMat,classifierOutput,character-method |
Compute the confusion matrix for a classifier. |
confuMat,classifierOutput,missing-method |
Compute the confusion matrix for a classifier. |
confuMat,classifierOutput-method |
Compute the confusion matrix for a classifier. |
confuMat,classifOutput,character-method |
Compute the confusion matrix for a classifier. |
confuMat,classifOutput,missing-method |
Compute the confusion matrix for a classifier. |
confuMat,classifOutput-method |
Compute the confusion matrix for a classifier. |
confuMat-methods |
Compute the confusion matrix for a classifier. |
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 |
DAB |
real adaboost (Friedman et al) |
daboostCont-class |
Class "raboostCont" ~~~ |
diana-class |
Class "classifOutput": container for output of classification procedures in R |
dianaB |
An interface to various unsupervised machine learning methods for ExpressionSets |
dianaB,ExpressionSet,numeric-method |
An interface to various unsupervised machine learning methods for ExpressionSets |
dist-class |
Class "classifOutput": container for output of classification procedures in R |
distMat |
An interface to various unsupervised machine learning methods for ExpressionSets |
distMat,MLOutput-method |
An interface to various machine learning methods for ExpressionSets |
dlda |
revised MLearn interface for machine learning |
dlda2 |
revised MLearn interface for machine learning |
dldaI |
revised MLearn interface for machine learning |
gbm-class |
Class "classifOutput": container for output of classification procedures in R |
gbmB |
An interface to various machine learning methods for ExpressionSets |
gbmB,ExpressionSet,character,integer-method |
An interface to various machine learning methods for ExpressionSets |
getGrid |
MLInterfaces infrastructure |
getGrid,data.frame-method |
MLInterfaces infrastructure |
getGrid,ExpressionSet-method |
MLInterfaces infrastructure |
getVarImp |
Class "varImpStruct" - collect data on variable importance from various machine learning methods |
getVarImp,classifierOutput,logical-method |
Class "varImpStruct" - collect data on variable importance from various machine learning methods |
getVarImp,classifierOutput,missing-method |
Class "varImpStruct" - collect data on variable importance from various machine learning methods |
getVarImp,classifOutput,logical-method |
Class "varImpStruct" - collect data on variable importance from various machine learning methods |
glmI.logistic |
revised MLearn interface for machine learning |
groupIndex-class |
Class "classifOutput": container for output of classification procedures in R |
Kfold |
for given n, generate a K-fold partition of 1:n |
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 |
knn.cv2 |
revised MLearn interface for machine learning |
knn.cvI |
revised MLearn interface for machine learning |
knn1B |
An interface to various machine learning methods for ExpressionSets |
knn1B,ExpressionSet,character,integer-method |
An interface to various machine learning methods for ExpressionSets |
knn2 |
revised MLearn interface for machine learning |
knnB |
An interface to various machine learning methods for ExpressionSets |
knnB,ExpressionSet,character,integer-method |
An interface to various machine learning methods for ExpressionSets |
knnI |
revised MLearn interface for machine learning |
knnP |
An interface to various machine learning methods for ExpressionSets |
knnP-class |
Class "classifOutput": container for output of classification procedures in R |
ksvmI |
revised MLearn interface for machine learning |
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 |
ldaI |
revised MLearn interface for machine learning |
learnerSchema-class |
Class "learnerSchema" - convey information on a machine learning function to the MLearn wrapper |
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 |
lvq |
revised MLearn interface for machine learning |
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 |
lvqI |
revised MLearn interface for machine learning |
makeLearnerSchema |
revised MLearn interface for machine learning |
membMat-class |
Class "classifOutput": container for output of classification procedures in R |
mkfmla |
real adaboost (Friedman et al) |
MLearn |
revised MLearn interface for machine learning |
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,data.frame,learnerSchema,numeric,missing-method |
revised MLearn interface for machine learning |
MLearn,formula,data.frame,learnerSchema,xvalSpec,missing-method |
revised MLearn interface for machine learning |
MLearn,formula,ExpressionSet,character,numeric,ANY-method |
Methods for Function MLearn in Package ‘MLInterfaces’ |
MLearn,formula,ExpressionSet,character,numeric,missing-method |
revised MLearn interface for machine learning |
MLearn,formula,ExpressionSet,character,numeric-method |
Methods for Function MLearn in Package ‘MLInterfaces’ |
MLearn,formula,ExpressionSet,learnerSchema,numeric,missing-method |
revised MLearn interface for machine learning |
MLearn,formula,ExpressionSet,learnerSchema,xvalSpec,missing-method |
revised MLearn interface for machine learning |
MLearn-methods |
Methods for Function MLearn in Package ‘MLInterfaces’ |
MLearn-OLD |
Methods for Function MLearn in Package ‘MLInterfaces’ |
MLearn_new |
revised MLearn interface for machine learning |
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 |
plotXvalRDA |
revised MLearn interface for machine learning |
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) |
Predict,daboostCont-method |
real adaboost (Friedman et al) |
Predict,raboostCont-method |
real adaboost (Friedman et al) |
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 |
RAB |
real adaboost (Friedman et al) |
rab |
revised MLearn interface for machine learning |
RAB4es |
real adaboost (Friedman et al) |
RABI |
revised MLearn interface for machine learning |
raboostCont-class |
Class "raboostCont" ~~~ |
randomForest-class |
Class "classifOutput": container for output of classification procedures in R |
randomForestB |
An interface to various machine learning methods for ExpressionSets |
randomForestB,ExpressionSet,character,integer-method |
An interface to various machine learning methods for ExpressionSets |
randomForestI |
revised MLearn interface for machine learning |
rdacvI |
revised MLearn interface for machine learning |
rdacvML |
revised MLearn interface for machine learning |
rdaI |
revised MLearn interface for machine learning |
rdaML |
revised MLearn interface for machine learning |
report |
Class "varImpStruct" - collect data on variable importance from various machine learning methods |
report,varImpStruct-method |
Class "varImpStruct" - collect data on variable importance from various machine learning methods |
RObject |
An interface to various machine learning methods for ExpressionSets |
RObject,classifierOutput-method |
Class "classifierOutput" |
RObject,MLOutput-method |
An interface to various machine learning methods for ExpressionSets |
rpart-class |
Class "classifOutput": container for output of classification procedures in R |
rpartB |
An interface to various machine learning methods for ExpressionSets |
rpartB,ExpressionSet,character,integer-method |
An interface to various machine learning methods for ExpressionSets |
rpartI |
revised MLearn interface for machine learning |
show,classifierOutput-method |
Class "classifierOutput" |
show,clustOutput-method |
Class "clustOutput" container for cluster analysis results |
show,learnerSchema-method |
Class "learnerSchema" - convey information on a machine learning function to the MLearn wrapper |
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 |
sldaI |
revised MLearn interface for machine learning |
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 |
standardMLIConverter |
revised MLearn interface for machine learning |
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 |
svmI |
revised MLearn interface for machine learning |
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 |
xvalSpec |
container for information specifying a cross-validated machine learning exercise |
xvalSpec-class |
container for information specifying a cross-validated machine learning exercise |