Bayesian Optimization for Experiments

Welcome to Bayesian Optimization for Experiments

This module is a continuation of the Bayesian Optimization module. Please follow along that module first in order to understand the basics of Bayesian optimization.

This time, you will enter your own parameters, optimization objective, and experimental data. Instructions can be seen below.

Process:

1. Input the amount of paramters you have in your experiment. Name them and give them ranges for optimization.
2. Name your optimization objective. Choose whether to maximize or minimize this objective.
3. Enter the number of experimental trials you have already carried out.
4. Either enter the values for the parameters and objective manually or upload a csv file with each column titled to mathc your paramters and objective with the objective in the last column. (Units should not matter as long as the units for each paramter or objective stays the sanme the whole time.
5. Choose your Surrogate Model and Acquisition Function. Lock your settings.
6. Click "Suggest Next Experiment." Carry out these parameters and then report the objective result in the box.
7. Click "Submit Result & Update Model." Repat Step 6 and this step until the objective is optimized.