BNNprior {BNN} | R Documentation |
Calculating the prior probability of linear and nonlinear classes of BNN models.
BNNprior(dimX, dimY, hid_num = 3,lambda=0.025,total_iteration=1000000,popN = 20)
dimX |
Dimension of the input data. |
dimY |
The dimension of reponse data. It is restricted to 1 in the current version of the package. |
hid_num |
Number of hidden units. The default setting is 3. |
lambda |
The prior probability for each connection of the neural network being selected for the final model. The default setting is 0.025. |
total_iteration |
Number of total iterations, default of 1000,000. |
popN |
Number of Markov Chains, default of 20. |
prob |
Prior probability assigned to the class of linear models. |
Bochao Jia and Faming Liang
Liang, F., Li, Q., and Zhou, L. (2017). Bayesian Neural Networks for Selection of Drug Sensitive Genes. Journal of the American Statistical Association.
library(BNN) BNNprior(50, 1, hid_num = 3, lambda=0.025, total_iteration = 10000, popN = 5)