opt.RMSProp {BayesFluxR}R Documentation

RMSProp optimiser

Description

RMSProp optimiser

Usage

opt.RMSProp(eta = 0.001, rho = 0.9, eps = 1e-08)

Arguments

eta

learning rate

rho

momentum

eps

not documented by Flux

Value

see opt.Descent

Examples

## Not run: 
  ## Needs previous call to `BayesFluxR_setup` which is time
  ## consuming and requires Julia and BayesFlux.jl
  BayesFluxR_setup(installJulia=TRUE, seed=123)
  net <- Chain(Dense(5, 1))
  like <- likelihood.feedforward_normal(net, Gamma(2.0, 0.5))
  prior <- prior.gaussian(net, 0.5)
  init <- initialise.allsame(Normal(0, 0.5), like, prior)
  x <- matrix(rnorm(5*100), nrow = 5)
  y <- rnorm(100)
  bnn <- BNN(x, y, like, prior, init)
  find_mode(bnn, opt.RMSProp(), 10, 100)

## End(Not run)


[Package BayesFluxR version 0.1.3 Index]