Welcome to HBayes’ Documentation

Overview

hbayes is a set of easy-to-use python development utilities.

Tutorials

• Installation

Best Practices

• Basic tour of the Bayesian Optimization package
  • 1. Specifying the function to be optimized
  • 2. Getting Started
  • 3. Guiding the optimization
  • 4. Saving, loading and restarting
  • Next Steps
• Advanced tour of the Bayesian Optimization package
  • 1. Suggest-Evaluate-Register Paradigm
  • 2. Dealing with discrete parameters
  • 3. Handling functions that may throw exceptions
  • 4. Tuning the underlying Gaussian Process
  • Observers Continued
• Sequential Domain Reduction
  • Background
  • Basics
  • Parameters
• Exploitation vs Exploration
  • Target function
  • Acquisition Function “Upper Confidence Bound”
  • Acquisition Function “Expected Improvement”
  • Acquisition Function “Probability of Improvement”
• Visualization
  • Target Function
  • Create a BayesianOptimization Object
  • Plotting and visualizing the algorithm at each step
  • Stopping

API Documentation

• hbayes.bayesian_optimization
  • Queue
  • BayesianOptimization
• hbayes.config
  • hbayes.config.meta
• hbayes.domain_reduction
  • TransformerCore
  • DomainTransformer
  • SDRCore
  • SequentialDomainReductionTransformer
• hbayes.event
  • OptimizationEvent
• hbayes.logger
  • StepTracker
  • ScreenLogger
  • JSONLogger
• hbayes.target_space
  • FuncFailed
  • TargetSpace
• hbayes.util
  • acq_max
  • UtilityFunction
  • load_logs
  • ensure_rng