Yet Another Probabilistic Neural Network

Documentation for package ‘yap’ version 0.1.1

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 on the cross entropy
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 on the cross entropy
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 in the PNN