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Releases: scikit-optimize/scikit-optimize
Releases · scikit-optimize/scikit-optimize
v0.3
Third time's a charm.
New features
- Accuracy improvements of the optimization of the acquisition function
by pre-selecting good candidates as starting points when
usingacq_optimizer='lbfgs'
. - Support a ask-and-tell interface. Check out the
Optimizer
class if you need
fine grained control over the iterations. - Parallelize L-BFGS minimization runs over the acquisition function.
- Implement weighted hamming distance kernel for problems with only categorical dimensions.
- New acquisition function
gp_hedge
that probabilistically chooses one ofEI
,PI
orLCB
at every iteration depending upon the cumulative gain.
Bug fixes
- Warnings are now raised if a point is chosen as the candidate optimum multiple
times. - Infinite gradients that were raised in the kernel gradient computation are
now fixed. - Integer dimensions are now normalized to [0, 1] internally in
gp_minimize
.
API Changes.
- The default
acq_optimizer
function has changed from"auto"
to"lbfgs"
ingp_minimize
.