Expand description
Learned Hyperparameter Tuner
Implementation of machine learning-based hyperparameter tuning that learns optimal hyperparameter configurations across different optimization problems.
Structs§
- Bayesian
Optimizer - Bayesian optimizer for hyperparameter search
- Categorical
Hyperparameter - Categorical hyperparameter
- Conditional
Dependency - Conditional dependency between parameters
- Continuous
Hyperparameter - Continuous hyperparameter
- Cost
Model - Cost model for evaluations
- Discrete
Hyperparameter - Discrete hyperparameter
- Evaluation
Record - Evaluation record
- Fidelity
Correlation Estimator - Correlation estimator between fidelities
- Fidelity
Level - Fidelity level definition
- Gaussian
Process - Gaussian process surrogate model
- Hyperparameter
Config - Hyperparameter configuration
- Hyperparameter
Space - Hyperparameter space definition
- Hyperparameter
Tuning Stats - Hyperparameter tuning statistics
- Learned
Hyperparameter Tuner - Learned hyperparameter tuner with adaptive configuration
- Multi
Fidelity Evaluator - Multi-fidelity evaluator
- Performance
Database - Performance database for storing evaluation results
- Performance
Trend - Performance trend analysis
- Resource
Requirements - Resource requirements for evaluation
Enums§
- Acquisition
Function - Acquisition function types
- Correlation
Method - Correlation estimation methods
- Dependency
Condition - Dependency condition types
- Fidelity
Selection Strategy - Fidelity selection strategy
- Kernel
Function - Kernel function types
- Mean
Function - Mean function for GP
- Optimization
Strategy - Optimization strategy for acquisition function
- Parameter
Scale - Parameter scale types
- Parameter
Value - Parameter value types
Functions§
- hyperparameter_
tuning_ optimize - Convenience function for learned hyperparameter tuning
- placeholder