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odbo source code descriptions

This folder contains the source codes for ODBO algorithms

  • bo.py: Naive Bayesian optimization to generate the next set of queries points
  • featurization.py: Generate the feature vectors for different scenarios of protein datasets
  • gp.py: Gauassian process regression model constructions, inclding the GP with GP likelihood and GP with studentT likelihood.
  • initialization.py: Algorithm to find suitable initial set of measurements to be measured in experiments
  • plot.py: Plotting functions to plot the confusion matrix for XGBOD accuracy and BO curves
  • prescreening.py: The XGBOD search space prescreening algorithm
  • regressions.py: Surrogate modeling with GP or RobustGP
  • run_exp.py: Wrapped functions to pack the BO search of each iteration
  • test.py: Test functions to make sure the package is installed correctly
  • turbo.py: Trust region Bayesian optimization algorithm to generate the next set of queries points
  • utils.py: Useful functions