| getConverter |
container for clustering outputs in uniform structure |
| getConverter,clusteringSchema-method |
container for clustering outputs in uniform structure |
| getDist |
container for clustering outputs in uniform structure |
| getDist,clusteringSchema-method |
container for clustering outputs in uniform structure |
| 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 |
MLInterfaces infrastructure |
| makeLearnerSchema |
revised MLearn interface for machine learning |
| membMat |
MLInterfaces infrastructure |
| mkfmla |
real adaboost (Friedman et al) |
| MLearn |
revised MLearn interface for machine learning |
| MLearn,formula,data.frame,clusteringSchema,ANY-method |
revised MLearn interface for machine learning |
| MLearn,formula,data.frame,learnerSchema,numeric-method |
revised MLearn interface for machine learning |
| MLearn,formula,data.frame,learnerSchema,xvalSpec-method |
revised MLearn interface for machine learning |
| MLearn,formula,ExpressionSet,character,numeric-method |
revised MLearn interface for machine learning |
| MLearn,formula,ExpressionSet,learnerSchema,numeric-method |
revised MLearn interface for machine learning |
| MLearn,formula,ExpressionSet,learnerSchema,xvalSpec-method |
revised MLearn interface for machine learning |
| MLearn_new |
revised MLearn interface for machine learning |
| MLLabel |
MLInterfaces infrastructure |
| MLOutput |
MLInterfaces infrastructure |
| MLScore |
MLInterfaces infrastructure |
| pamI |
revised MLearn interface for machine learning |
| planarPlot |
Methods for Function planarPlot in Package ‘MLInterfaces’ |
| planarPlot,classifierOutput,data.frame,character-method |
Methods for Function planarPlot in Package ‘MLInterfaces’ |
| planarPlot,classifierOutput,ExpressionSet,character-method |
Methods for Function planarPlot in Package ‘MLInterfaces’ |
| planarPlot-methods |
Methods for Function planarPlot in Package ‘MLInterfaces’ |
| plot,clusteringOutput,ANY-method |
container for clustering outputs in uniform structure |
| 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 |
| Predict |
real adaboost (Friedman et al) |
| Predict,daboostCont-method |
real adaboost (Friedman et al) |
| Predict,raboostCont-method |
real adaboost (Friedman et al) |
| probArray |
MLInterfaces infrastructure |
| probMat |
MLInterfaces infrastructure |
| 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" ~~~ |
| 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 |
Class "classifierOutput" |
| RObject,classifierOutput-method |
Class "classifierOutput" |
| RObject,clusteringOutput-method |
container for clustering outputs in uniform structure |
| rpartI |
revised MLearn interface for machine learning |