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| append.overwrite.alists | Combine two argument lists |
| as.numeric.factor | Convert a factor to numeric.vector. |
| box.outliers | Box Outliers |
| convolute_ff | Cross-validated main effects interpretation for all feature contributions. |
| convolute_ff2 | Low-level function to estimate a specific set of feature contributions by corresponding features with kknn-package. Used to estimate goodness-of-fit of surface in show3d. |
| convolute_grid | Model structure grid estimated by feature contributions |
| fcol | Generic colour module for forestFloor objects |
| forestFloor | Compute out-of-bag cross-validated feature contributions to visualize model structures of randomForest models. |
| forestFloorPackage | forestFloor: visualize the random forest model structure |
| forestFloor_randomForest_classification | Compute out-of-bag cross-validated feature contributions to visualize model structures of randomForest models. |
| forestFloor_randomForest_regression | Compute out-of-bag cross-validated feature contributions to visualize model structures of randomForest models. |
| importanceExportWrapper | Importance Export Wrapper (internal) |
| multiTree | recursiveTree: cross-validated feature contributions |
| plot.forestFloor | plot.forestFloor_regression |
| plot.forestFloor_multiClass | plot.forestFloor_regression |
| plot.forestFloor_regression | plot.forestFloor_regression |
| plot_simplex3 | 3-class simplex forestFloor plot |
| print.forestFloor | print summary of forestFloor.Object |
| print.forestFloor_classification | print summary of forestFloor.Object |
| print.forestFloor_multiClass | print summary of forestFloor.Object |
| print.forestFloor_regression | print summary of forestFloor.Object |
| recTree | recursiveTree: cross-validated feature contributions |
| show3d | make forestFloor 3D-plot of random forest feature contributions |
| show3d.forestFloor_multiClass | make forestFloor 3D-plot of random forest feature contributions |
| show3d.forestFloor_regression | make forestFloor 3D-plot of random forest feature contributions |
| vec.plot | Compute and plot vector effect characteristics for a given multivariate model |
| Xtestmerger | merge training set (X) and (test) set |