find_mode {BayesFluxR}

Find the MAP of a BNN using SGD

Description

Find the MAP of a BNN using SGD

Usage

find_mode(bnn, optimiser, batchsize, epochs)

Arguments

bnn

a BNN obtained using BNN

optimiser

an optimiser. These start with 'opt.'. See for example opt.ADAM

batchsize

batch size

epochs

number of epochs to run for

Value

Returns a vector. Use posterior_predictive to obtain a prediction using this MAP estimate.

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)