doc: gpopt
Sequential optimization using GP algorithms
Syntax
[queries, Yt] = gpopt(f, Xt, Yt, Xs, T) [queries, Yt] = gpopt(..., 'Name',Value)
Arguments
- f function which returns observations
- Xt matrix (nt, d) of initial data
- Yt vector (nt, 1) of initial observations
- Xs matrix (ns, d) of search data
- T integer for the number of iterations
Name-Value Pair Arguments
- algo string code for the query algorithm possible values are 'gpucb' (default), 'chaining', 'ei' for purely sequential optimization and 'gpucbpe', 'greedyucb' for batch sequential optimization
- noise scalar for the noise standard deviation (default: 1e-2)
- u scalar for the negative logarithm of the upper bound probability (default: 3)
- B integer for the size of the batch in batch sequential optimization (default: 1)
- kernel kernel function for the inferance (default: @kernel_se_normiso)
- basis basis function for the inferance (default: @basis_none)
- Kss matrix (ns,ns) of the kernel between points of Xs, used by the 'chaining' algorithm
- plot boolean to visualize the optimization (default: false)
- verbose boolean to monitor the optimization (default: true)
Outputs
- queries vector (1,T) of queries indices
- Yt vector (T,1) of observations