Man pages for yap
Yet Another Probabilistic Neural Network
| dummies | Convert a N-category vector to a N-dimension matrix |
| 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 |
| logl | Calculate the multiclass cross-entropy |
| pnn.fit | Create a probabilistic neural network |
| pnn.imp | Derive the importance rank of all predictors used in the PNN |
| pnn.optmiz_logl | Optimize the optimal value of PNN smoothing parameter based... |
| pnn.parpred | Calculate predicted probabilities of PNN by using parallelism |
| pnn.pfi | Derive the PFI rank of all predictors used in the PNN |
| pnn.predict | Calculate a matrix of predicted probabilities |
| pnn.predone | Calculate the predicted probability for each category of PNN |
| pnn.search_logl | Search for the optimal value of PNN smoothing parameter based... |
| pnn.x_imp | Derive the importance of a predictor used in the PNN |
| pnn.x_pfi | Derive the permutation feature importance of a predictor used... |
