Sequential Parameter Optimization Toolbox
Thomas Bartz-Beielstein tbb@bartzundbartz.de
SPOT uses a combination statistic models and optimization algorithms for the purpose of parameter optimization. Design of Experiment methods are employed to generate an initial set of candidate solutions, which are evaluated with a user-provided objective function. The resulting data is used to fit a model, which in turn is subject to an optimization algorithm, to find the most promising candidate solution(s). These are again evaluated, after which the model is updated with the new results. This sequential procedure of modeling, optimization and evaluation is iterated until the evaluation budget is exhausted.
Note, that versions >= 2.0.1 of the package are a complete rewrite of the interfaces and conventions in SPOT. The rewritten SPOT package aims to improve the following issues of the older package: - A more modular architecture is provided, that allows the user to easily customize parts of the SPO procedure. - Core functions for modeling and optimization use interfaces more similar to algorithms from other packages / core-R, hence making them easier accessible for new users. Also, these can now be more easily used separately from the main SPO approach, e.g., only for modeling. - Reducing the unnecessarily large number of choices and parameters. - Removal of extremely rarely used / un-used features, to reduce overall complexity of the package. - Improving documentation and accessibility in general. - Speed-up of frequently used procedures. We appreciate feedback about any bugs or other issues with the package. Feel free to send feedback by mail to the maintainer.
Main interface function is spot.