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| HieRanFor-package | HieRanFor: A package for running a hierarchical randomForest analysis. |
| GetMultPropVotes | For each case, the multiplicative proportion of votes |
| HieFMeasure | Hierarchical precision, hierarchical recall and hierarchical F measure |
| ImportanceHie | The importance value of each explanatory variable in each local classifier |
| JoinLevels | Combines the factor levels of two input vectors |
| OliveOilHie | Modification of the 'oliveoil' data-set from package 'pdfCluster'. |
| PerformanceFlatRF | Runs a flat classification on the same data as 'hie.RF' and assess performance. |
| PerformanceHRF | Flat and hierarchical performance measures. |
| PerformanceNewHRF | Predict and assess performance of 'new.data', for which the 'true' class is known. |
| plot.HRF | Plot the Hierarchical class structure |
| PlotImportanceHie | Plotting function for the hierarchical importance |
| predict.HRF | For all cases, the proportion of OOB votes that each class received in each local randomForest classifier. |
| PredictNewHRF | Predict crisp class for 'new.data' |
| RandomHRF | Create random class hierarchy with random training and 'new.data' cases. |
| RunHRF | Run the Hierarchical randomForest on the training data. |
| tuneRF2 | the tuneRF function of randomForest after correcting for error relating to errorOld=0 |