User should be able to determine acquisition function for respective execution strategies.
from mlr MBO documentation:
setMBOControlInfill(): It is recommended to set the infill criterion. For learners that support
"predict.type=se", the Confidence Bound "cb" and the Expected Improvement "ei" are a good choice.
see: https://mlr-org.github.io/mlrMBO/reference/infillcrits.html
from skopt documentation:
parameter: acq_func [string, default="LCB"]: Function to minimize over the forest posterior. Can be either:
"LCB" for lower confidence bound.
"EI" for negative expected improvement.
"PI" for negative probability of improvement.
`"EIps" for negated expected improvement per second to take into account the function compute time. Then, the objective function is assumed to return two values, the first being the objective value and the second being the time taken in seconds.
"PIps" for negated probability of improvement per second. The return type of the objective function is assumed to be similar to that of "EIps"
alinaciuysal
commented
6 years ago
User should be able to determine acquisition function for respective execution strategies.
from mlr MBO documentation: setMBOControlInfill(): It is recommended to set the infill criterion. For learners that support "predict.type=se", the Confidence Bound "cb" and the Expected Improvement "ei" are a good choice. see: https://mlr-org.github.io/mlrMBO/reference/infillcrits.html
from skopt documentation: