Crate sklears_calibration

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Probability calibration for classifiers

This module provides methods to calibrate classifier probabilities, making them more reliable and well-calibrated.

Modules§

advanced: Advanced calibration methods including conformal prediction, Bayesian approaches, and domain-specific techniques Advanced calibration methods for sophisticated probability calibration
bayesian: Bayesian calibration methods including model averaging, variational inference, and MCMC Bayesian calibration methods
bbq: Bayesian binning into quantiles implementation for calibration Bayesian Binning into Quantiles (BBQ) for probability calibration
beta: Beta calibration and ensemble methods Beta calibration for probability calibration
binary: Binary calibration methods for probability calibration Binary calibration methods for probability calibration
calibration_aware_training: Calibration-aware training methods for machine learning models Calibration-aware training methods for machine learning models
category_theoretic: Category-theoretic calibration framework using functors, natural transformations, and categorical constructions Category-Theoretic Calibration Framework
conformal: Conformal prediction methods for uncertainty quantification Conformal prediction methods for uncertainty quantification
continual_learning: Continual learning calibration methods Continual Learning Calibration Methods
core: Core types and error handling for calibration Core types and error handling for the calibration framework
differential_privacy: Differential privacy-preserving calibration methods Differential Privacy-Preserving Calibration Methods
domain_specific: Domain-specific calibration methods for time series, regression, ranking, and survival analysis Domain-specific calibration methods
fluent_api: Fluent API for calibration configuration Fluent API for calibration configuration
gaussian_process: Gaussian process calibration Gaussian Process calibration
gpu_calibration: GPU-accelerated calibration methods GPU-accelerated calibration methods
high_precision: High-precision arithmetic utilities for improved numerical stability High-precision arithmetic utilities for improved numerical stability
higher_order_uncertainty: Higher-order uncertainty decomposition beyond traditional epistemic/aleatoric dichotomy Higher-Order Uncertainty Decomposition Framework
histogram: Histogram binning implementation for calibration Histogram binning for probability calibration
information_geometry: Information geometric framework applying differential geometry to probability calibration Information Geometric Framework for Calibration
isotonic: Isotonic regression implementation for calibration Isotonic regression for probability calibration
kde: Kernel density estimation calibration Kernel Density Estimation (KDE) calibration
large_scale: Large-scale calibration methods for distributed computing and memory-efficient processing Large-scale calibration methods
llm_calibration: Large Language Model (LLM) specific calibration methods Large Language Model (LLM) Specific Calibration Methods
local: Local calibration methods Local calibration methods for spatially-aware probability calibration
measure_theoretic: Measure-theoretic advanced calibration framework using sigma-algebras, Radon-Nikodym derivatives, and martingale theory Measure-Theoretic Advanced Calibration Framework
meta_learning: Meta-learning calibration methods for automated method selection and differentiable ECE optimization Meta-Learning for Calibration
metrics: Calibration evaluation metrics module Calibration evaluation metrics
modular_framework: Enhanced modular framework for composable calibration strategies and pluggable modules Enhanced modular framework for calibration
multi_modal: Multi-modal calibration methods for cross-modal and heterogeneous ensemble calibration Multi-Modal Calibration Methods
multiclass: Multi-class calibration methods Multi-class calibration methods
neural_calibration: Neural network calibration layers for deep learning integration Neural network calibration layers for deep learning integration
numerical_stability: Numerical stability utilities and improvements Numerical stability utilities and improvements for calibration methods
optimization: Advanced optimization techniques for calibration including gradient-based and multi-objective methods Advanced optimization techniques for calibration
performance: Performance optimizations and SIMD support for calibration methods Performance Optimizations for Calibration Methods
prediction_intervals: Prediction intervals for uncertainty quantification Prediction intervals for uncertainty quantification
quantum_optimization: Quantum-inspired optimization algorithms for calibration parameter tuning Quantum-Inspired Optimization for Calibration
statistical_tests: Statistical validity tests for calibration methods Statistical validity tests for calibration methods
streaming: Streaming and online calibration methods for real-time applications Streaming and Online Calibration Methods
temperature: Temperature scaling implementation for calibration Temperature scaling for probability calibration
theoretical_validation: Theoretical calibration validation framework with mathematical proofs and bounds Theoretical Calibration Validation Framework
topological_calibration: Topological data analysis framework for calibration using persistent homology and simplicial complexes Topological Data Analysis Framework for Calibration
ultra_precision: Ultra-high precision mathematical framework for theoretical calibration validation Ultra-High Precision Mathematical Framework for Calibration
uncertainty_estimation: Epistemic and aleatoric uncertainty estimation Epistemic and aleatoric uncertainty estimation
validation: Validation framework for calibration methods Validation Framework for Calibration Methods
visualization: Visualization tools for calibration Visualization tools for calibration analysis

Structs§

CalibratedClassifierCV: Calibrated Classifier with Cross-Validation
CalibratedClassifierCVConfig: Configuration for CalibratedClassifierCV

Enums§

CalibrationMethod: Calibration methods

Traits§

CalibrationEstimator: Trait for calibration estimators

Crate sklears_calibration

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Modules§

Structs§

Enums§

Traits§

Crate sklears_calibration