Yet Another Probabilistic Neural Network

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Documentation for package ‘yap’ version 0.1.1

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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