Man pages for yager
Yet Another General Regression Neural Network
| folds | Generate a list of index for the n-fold cross-validation |
| gen_latin | Generate random numbers of latin hypercube sampling |
| gen_sobol | Generate sobol sequence |
| gen_unifm | Generate Uniform random numbers |
| grnn.fit | Create a general regression neural network |
| grnn.imp | Derive the importance rank of all predictors used in the GRNN |
| grnn.margin | Derive the marginal effect of a predictor used in a GRNN |
| grnn.optmiz_auc | Optimize the optimal value of GRNN smoothing parameter based... |
| grnn.parpred | Calculate predicted values of GRNN by using parallelism |
| grnn.partial | Derive the partial effect of a predictor used in a GRNN |
| grnn.pfi | Derive the PFI rank of all predictors used in the GRNN |
| grnn.predict | Calculate predicted values of GRNN |
| grnn.predone | Calculate a predicted value of GRNN |
| grnn.search_auc | Search for the optimal value of GRNN smoothing parameter... |
| grnn.search_rsq | Search for the optimal value of GRNN smoothing parameter... |
| grnn.x_imp | Derive the importance of a predictor used in the GRNN |
| grnn.x_pfi | Derive the permutation feature importance of a predictor used... |
