Expand description
Advanced Validation Framework for Kernel Approximation Methods
This module provides comprehensive validation tools including theoretical error bound validation, convergence analysis, and approximation quality assessment.
Structs§
- Cross
Validation Result - Cross-validation result for kernel approximation CrossValidationResult
- Dimension
Dependency Analysis - Dimension dependency analysis DimensionDependencyAnalysis
- Kernel
Approximation Validator - Comprehensive validation framework for kernel approximation methods KernelApproximationValidator
- Sample
Complexity Analysis - Sample complexity analysis SampleComplexityAnalysis
- Stability
Analysis - Stability analysis results StabilityAnalysis
- Theoretical
Bound - Theoretical error bounds for different approximation methods TheoreticalBound
- Validation
Config - Configuration for validation ValidationConfig
- Validation
Result - Result of validation analysis ValidationResult
Enums§
- Bound
Function - Functions for computing theoretical bounds BoundFunction
- Bound
Type - Types of theoretical bounds BoundType
Traits§
- Validatable
Kernel Method - Trait for kernel methods that can be validated
- Validated
Fitted Method - Trait for fitted methods that can be validated