Module hyperparameter_optimization 

Hyperparameter optimization for SVM algorithms

This module provides comprehensive hyperparameter optimization utilities for SVM models, including grid search, random search, and Bayesian optimization approaches.

Methods included:

• Grid Search: Exhaustive search over parameter grid
• Random Search: Random sampling from parameter distributions
• Bayesian Optimization: Gaussian Process-based optimization
• Evolutionary Algorithms: Genetic algorithm for parameter search
• Cross-validation integration for robust evaluation

Re-exports

pub use bayesian_optimization::BayesianOptimizationCV;

pub use evolutionary_optimization::EvolutionaryOptimizationCV;

pub use grid_search::GridSearchCV;

pub use random_search::RandomSearchCV;

Modules

bayesian_optimization

Bayesian Optimization for hyperparameter tuning

evolutionary_optimization

Evolutionary Algorithms for hyperparameter optimization

grid_search

Grid Search Cross-Validation for hyperparameter optimization

random_search

Random Search Cross-Validation for hyperparameter optimization

Structs

OptimizationConfig

Configuration for optimization algorithms

OptimizationResult

Optimization result

ParameterSet

Parameter set for SVM

SearchSpace

Hyperparameter search space

Enums

ParameterSpec

Parameter specification for optimization

ScoringMetric

Scoring metrics for evaluation