The implementation of BOMI in the paper 'Bayesian Optimization with Missing Inputs', ECMLPKDD2020.
- Python 3.6
- Numpy 1.18
- Scipy 1.3.1
- Scikit-learn 0.21.2
- Torch 1.3.1 (CUDA v9.2)
- Gpytorch 1.0.1
- Missingpy 0.2.0
- Pandas 0.25.3
(Optional)
- pip 19.3.1
- pillow 5.4.1
- Execute an experiment with the command: ..\python runExperiment <opt_method> <obj_function> <num_of_GPs> <alpha_param> <miss_rate> <miss_noise>
Example:
python runExperiemnt BOMI Eggholder2d 5 1e2 0.25 0.05
See 'runExperiment.py' for more details and see 'ndfunction.py' for how to define a new objective function.
Apache 2.0