Crate sklears_inspection 

Model inspection and interpretation tools

This crate provides comprehensive tools for understanding and interpreting machine learning models, including feature importance, partial dependence plots, SHAP values, counterfactual explanations, anchors, model complexity analysis, and model-agnostic explanations.

Re-exports

pub use types::explanation_methods;

pub use types::explanation_states;

pub use types::ExplanationConfig;

pub use types::ExplanationConstraint;

pub use types::ExplanationMethodValidator;

pub use types::ExplanationProperties;

pub use types::ExplanationValidator;

pub use types::FeatureImportanceConstraint;

pub use types::FixedSizeExplanation;

pub use types::GlobalGradientConfig;

pub use types::GlobalModelAgnosticConfig;

pub use types::GradientCompatible;

pub use types::LimeCompatible;

pub use types::LocalGradientConfig;

pub use types::LocalModelAgnosticConfig;

pub use types::ModelIntrospectable;

pub use types::ShapCompatible;

pub use types::ShapConstraint;

pub use types::TypedExplanation;

pub use adversarial::analyze_explanation_stability;

pub use adversarial::compute_certified_robustness;

pub use adversarial::generate_adversarial_examples;

pub use adversarial::test_explanation_robustness;

pub use adversarial::AdversarialAttack;

pub use adversarial::AdversarialConfig;

pub use adversarial::AdversarialExampleResult;

pub use adversarial::CertificationMethod;

pub use adversarial::CertifiedRobustnessResult;

pub use adversarial::ExplanationRobustnessResult;

pub use adversarial::RobustnessMetric;

pub use adversarial::StabilityAnalysisResult;

pub use adversarial::StabilityTrend;

pub use adversarial::VerificationStatus;

pub use anchors::explain_with_anchors;

pub use anchors::AnchorsConfig;

pub use attention::analyze_attention;

pub use attention::compute_gradcam;

pub use attention::dissect_network;

pub use attention::maximize_activation;

pub use attention::visualize_features;

pub use attention::ActivationMaximizationResult;

pub use attention::AttentionAnalyzer;

pub use attention::AttentionConfig;

pub use attention::AttentionResult;

pub use attention::AttentionType;

pub use attention::FeatureVisualizationResult;

pub use attention::GradCAMConfig;

pub use attention::GradCAMResult as AttentionGradCAMResult;

pub use attention::NetworkDissectionResult;

pub use benchmarking::BenchmarkCategory;

pub use benchmarking::BenchmarkConfig;

pub use benchmarking::BenchmarkReport;

pub use benchmarking::BenchmarkResult;

pub use benchmarking::BenchmarkingSuite;

pub use benchmarking::CategorySummary;

pub use benchmarking::InsightSeverity;

pub use benchmarking::InsightType;

pub use benchmarking::MemoryStatistics;

pub use benchmarking::PerformanceInsight;

pub use benchmarking::ProblemType;

pub use benchmarking::QualityMetrics;

pub use benchmarking::ReferenceComparison;

pub use benchmarking::TestConfiguration;

pub use benchmarking::TimingStatistics;

pub use builder::ComparisonResult;

pub use builder::ComparisonResults;

pub use builder::ComparisonStudy;

pub use builder::ComparisonStudyBuilder;

pub use builder::CounterfactualConfig as BuilderCounterfactualConfig;

pub use builder::ExplanationBuilder;

pub use builder::ExplanationPipelineExecutor;

pub use builder::FeatureSelection;

pub use builder::LimeConfig;

pub use builder::OptimizationMethod;

pub use builder::PermutationConfig as BuilderPermutationConfig;

pub use builder::PipelineBuilder;

pub use builder::PipelineExecutionResult;

pub use builder::PipelineStep;

pub use builder::ScoreFunction as BuilderScoreFunction;

pub use builder::ShapConfig;

pub use builder::StepMetadata;

pub use causal::analyze_instrumental_variables;

pub use causal::analyze_mediation;

pub use causal::apply_do_calculus;

pub use causal::discover_causal_structure;

pub use causal::estimate_causal_effect;

pub use causal::CausalConfig;

pub use causal::CausalEffectMethod;

pub use causal::CausalEffectResult;

pub use causal::CausalGraph;

pub use causal::InstrumentalVariableResult;

pub use causal::MediationResult;

pub use complexity::analyze_model_complexity;

pub use complexity::ComplexityConfig;

pub use computer_vision::explain_image_with_lime;

pub use computer_vision::explain_object_detection;

pub use computer_vision::explain_segmentation;

pub use computer_vision::generate_gradcam;

pub use computer_vision::generate_saliency_map;

pub use computer_vision::ComputerVisionConfig;

pub use computer_vision::DetectedObject;

pub use computer_vision::GradCAMResult;

pub use computer_vision::GradCAMStats;

pub use computer_vision::Image;

pub use computer_vision::ImageLimeResult;

pub use computer_vision::KeyFeature;

pub use computer_vision::ObjectDetectionExplanation;

pub use computer_vision::SaliencyMapResult;

pub use computer_vision::SaliencyMethod;

pub use computer_vision::SegmentExplanation;

pub use computer_vision::SegmentationExplanation;

pub use computer_vision::Superpixel;

pub use counterfactual::generate_actionable_counterfactual;

pub use counterfactual::generate_causal_counterfactual;

pub use counterfactual::generate_counterfactual;

pub use counterfactual::generate_diverse_counterfactuals;

pub use counterfactual::generate_feasible_counterfactual;

pub use counterfactual::generate_nearest_counterfactual;

pub use counterfactual::CounterfactualConfig;

pub use counterfactual::FeasibilityConfig;

pub use dashboard::Alert;

pub use dashboard::AlertSeverity;

pub use dashboard::AlertThresholds;

pub use dashboard::AlertType;

pub use dashboard::Dashboard;

pub use dashboard::DashboardConfig;

pub use dashboard::DashboardDataPoint;

pub use dashboard::DashboardLayout;

pub use dashboard::DashboardState;

pub use dashboard::DashboardTheme;

pub use dashboard::DashboardUpdate;

pub use dashboard::WidgetConfig;

pub use dashboard::WidgetType;

pub use deep_learning::ConceptActivationVector;

pub use deep_learning::ConceptDatabase;

pub use deep_learning::ConceptDiscoveryMethod;

pub use deep_learning::ConceptHierarchy;

pub use deep_learning::DeepLearningAnalyzer;

pub use deep_learning::DeepLearningConfig;

pub use deep_learning::DetectedConcept;

pub use deep_learning::DisentanglementMetrics;

pub use deep_learning::NetworkDissectionResult as DeepNetworkDissectionResult;

pub use deep_learning::TCAVResult;

pub use distributed::ClusterConfig;

pub use distributed::ClusterExplanationOrchestrator;

pub use distributed::ClusterHealth;

pub use distributed::ClusterStatistics;

pub use distributed::DistributedCoordinator;

pub use distributed::DistributedTask;

pub use distributed::HealthStatus;

pub use distributed::LoadBalancingStrategy;

pub use distributed::TaskResult;

pub use distributed::TaskStatus;

pub use distributed::TaskType;

pub use distributed::WorkerConfig;

pub use distributed::WorkerNode;

pub use enterprise::AccessControl;

pub use enterprise::AccessControlConfig;

pub use enterprise::AccessLevel;

pub use enterprise::ActionItem;

pub use enterprise::AlertRule;

pub use enterprise::AuditEvent;

pub use enterprise::AuditEventType;

pub use enterprise::AuditLogger;

pub use enterprise::AuditRecord;

pub use enterprise::AuditSeverity;

pub use enterprise::AuditTrail;

pub use enterprise::ComplianceFramework;

pub use enterprise::ComplianceReport;

pub use enterprise::ComplianceReporter;

pub use enterprise::ComplianceRule;

pub use enterprise::ComplianceStatus;

pub use enterprise::EnterpriseConfig;

pub use enterprise::ExplanationLineage;

pub use enterprise::ExplanationQualityMonitor;

pub use enterprise::LineageNode;

pub use enterprise::LineageRelation;

pub use enterprise::LineageTracker;

pub use enterprise::OperationType;

pub use enterprise::Permission;

pub use enterprise::PermissionSet;

pub use enterprise::QualityAlert;

pub use enterprise::QualityDataPoint;

pub use enterprise::QualityLevel;

pub use enterprise::QualityMetric;

pub use enterprise::QualityMonitorConfig;

pub use enterprise::QualityStatistics;

pub use enterprise::QualityThreshold;

pub use enterprise::QualityTrend;

pub use enterprise::QualityTrendDirection;

pub use enterprise::RegulatoryRequirement;

pub use enterprise::RiskLevel;

pub use enterprise::Role;

pub use enterprise::RoleManager;

pub use enterprise::SecureExplanationExecutor;

pub use enterprise::SecurityContext;

pub use enterprise::User;

pub use enterprise::UserGroup;

pub use external_visualizations::D3Backend;

pub use external_visualizations::D3Config;

pub use external_visualizations::PlotlyBackend;

pub use external_visualizations::PlotlyConfig;

pub use external_visualizations::PlotlyPlotConfig;

pub use external_visualizations::VegaLiteBackend;

pub use external_visualizations::VegaLiteConfig;

pub use external_visualizations::VegaLiteDefaultConfig;

pub use fairness::analyze_demographic_parity;

pub use fairness::analyze_equalized_odds;

pub use fairness::analyze_individual_fairness;

pub use fairness::assess_fairness;

pub use fairness::compute_group_fairness_metrics;

pub use fairness::detect_bias;

pub use fairness::BiasDetectionResult;

pub use fairness::DemographicParityResult;

pub use fairness::DistanceMetric;

pub use fairness::EqualizedOddsResult;

pub use fairness::FairnessConfig;

pub use fairness::FairnessMetrics;

pub use fairness::FairnessResult;

pub use fairness::IndividualFairnessResult;

pub use federated::AggregationStats;

pub use federated::FederatedConfig;

pub use federated::FederatedExplainer;

pub use federated::FederatedExplanation;

pub use federated::PrivacyMechanism;

pub use framework::ChainedConfig;

pub use framework::ChainedStrategy;

pub use framework::CombinedConfig;

pub use framework::CombinedOutput;

pub use framework::CombinedStrategy;

pub use framework::CounterfactualExplainer;

pub use framework::Explainer;

pub use framework::ExplanationMetadata;

pub use framework::ExplanationPipeline;

pub use framework::ExplanationPostProcessor;

pub use framework::ExplanationStrategy;

pub use framework::FeatureAttributor;

pub use framework::FeatureExplainer;

pub use framework::GlobalExplainer;

pub use framework::GradientAttributor;

pub use framework::LocalExplainer;

pub use framework::PipelineResult;

pub use framework::UncertainExplanation;

pub use framework::UncertaintyAwareExplainer;

pub use framework::ValidationResult;

pub use framework::ValidationViolation;

pub use framework::ViolationSeverity;

pub use gnn::GNNExplainer;

pub use gnn::GNNExplainerConfig;

pub use gnn::GNNExplanation;

pub use gnn::GNNTask;

pub use gnn::Graph;

pub use gnn::MessagePassingExplanation;

pub use gpu::utils as gpu_utils;

pub use gpu::GpuBackend;

pub use gpu::GpuBuffer;

pub use gpu::GpuConfig;

pub use gpu::GpuContext;

pub use gpu::GpuDevice;

pub use gpu::GpuExplanationComputer;

pub use gpu::GpuPerformanceStats;

pub use hooks::CustomEvent;

pub use hooks::ErrorInfo;

pub use hooks::ExecutionMetrics;

pub use hooks::ExplanationHook;

pub use hooks::HookContext;

pub use hooks::HookEvent;

pub use hooks::HookRegistry;

pub use hooks::HookRegistryStatistics;

pub use hooks::HookResult;

pub use hooks::HookedExplanationExecutor;

pub use hooks::LogLevel;

pub use hooks::LoggingHook;

pub use hooks::MemoryInfo;

pub use hooks::MetricsHook;

pub use hooks::ProgressInfo;

pub use hooks::TimingInfo;

pub use information_theoretic::analyze_information_bottleneck;

pub use information_theoretic::analyze_mutual_information;

pub use information_theoretic::apply_minimum_description_length;

pub use information_theoretic::compute_information_gain_attribution;

pub use information_theoretic::generate_entropy_explanations;

pub use information_theoretic::EntropyExplanationResult;

pub use information_theoretic::EstimationMethod;

pub use information_theoretic::InformationBottleneckResult;

pub use information_theoretic::InformationGainResult;

pub use information_theoretic::InformationTheoreticConfig;

pub use information_theoretic::MDLResult;

pub use information_theoretic::MutualInformationResult;

pub use lazy::LazyComputationManager;

pub use lazy::LazyConfig;

pub use lazy::LazyExecutionStats;

pub use lazy::LazyExplanation;

pub use lazy::LazyExplanationPipeline;

pub use lazy::LazyFeatureImportance;

pub use lazy::LazyShapValues;

pub use llm::CounterfactualText;

pub use llm::LLMAttentionExplanation;

pub use llm::LLMExplainer;

pub use llm::LLMExplainerConfig;

pub use llm::LLMExplanation;

pub use llm::LLMTask;

pub use llm::LayerImportance;

pub use llm::LayerType;

pub use llm::NeuronActivation;

pub use llm::PromptSensitivity;

pub use llm::PromptVariation;

pub use llm::TokenizedInput;

pub use llm::VariationType;

pub use local_explanations::explain_locally;

pub use local_explanations::LocalExplanationConfig;

pub use local_explanations::LocalExplanationMethod;

pub use memory::cache_friendly_permutation_importance;

pub use memory::cache_friendly_shap_computation;

pub use memory::CacheConfig;

pub use memory::CacheKey;

pub use memory::CacheStatistics;

pub use memory::ExplanationCache;

pub use memory::ExplanationDataLayout;

pub use memory::MemoryLayoutManager;

pub use metrics_registry::CompletenessMetric;

pub use metrics_registry::ComputationMetadata;

pub use metrics_registry::ComputationalComplexity;

pub use metrics_registry::ExplanationData;

pub use metrics_registry::ExplanationMetric;

pub use metrics_registry::ExplanationType;

pub use metrics_registry::FidelityMetric;

pub use metrics_registry::MetricCategory;

pub use metrics_registry::MetricInput;

pub use metrics_registry::MetricMetadata;

pub use metrics_registry::MetricOutput;

pub use metrics_registry::MetricProperties;

pub use metrics_registry::MetricRegistry;

pub use metrics_registry::RegistryStatistics;

pub use metrics_registry::StabilityMetric;

pub use model_agnostic::explain_model_agnostic;

pub use model_agnostic::ModelAgnosticConfig;

pub use model_comparison::analyze_ensemble;

pub use model_comparison::assess_prediction_stability;

pub use model_comparison::compare_models;

pub use model_comparison::compute_model_agreement;

pub use model_comparison::BiasVarianceDecomposition;

pub use model_comparison::DiversityMetrics;

pub use model_comparison::EnsembleAnalysisResult;

pub use model_comparison::EnsembleMethod;

pub use model_comparison::ModelComparisonConfig;

pub use model_comparison::ModelComparisonResult;

pub use model_comparison::ModelMetrics;

pub use model_comparison::StabilityMetrics;

pub use multimodal::CrossModalAttention;

pub use multimodal::FusionExplanation;

pub use multimodal::FusionStrategy;

pub use multimodal::InteractionType;

pub use multimodal::ModalityContributions;

pub use multimodal::ModalityInteraction;

pub use multimodal::ModalityType;

pub use multimodal::MultiModalConfig;

pub use multimodal::MultiModalExplainer;

pub use multimodal::MultiModalExplanation;

pub use multimodal::MultiModalInput;

pub use nlp::analyze_text_attention;

pub use nlp::explain_semantic_similarity;

pub use nlp::explain_syntax;

pub use nlp::explain_text_with_lime;

pub use nlp::visualize_word_importance;

pub use nlp::AttentionExplanation;

pub use nlp::AttentionPattern;

pub use nlp::AttentionPatternType;

pub use nlp::NLPConfig;

pub use nlp::SemanticCluster;

pub use nlp::SemanticExplanation;

pub use nlp::SemanticRelation;

pub use nlp::SyntacticExplanation;

pub use nlp::SyntacticNode;

pub use nlp::SyntacticPattern;

pub use nlp::SyntacticTree;

pub use nlp::Token;

pub use nlp::WordImportanceResult;

pub use occlusion::analyze_occlusion;

pub use occlusion::OcclusionConfig;

pub use occlusion::OcclusionMethod;

pub use parallel::compute_shap_parallel;

pub use parallel::process_batches_optimized;

pub use parallel::process_batches_parallel;

pub use parallel::AdaptiveBatchConfig;

pub use parallel::BatchConfig;

pub use parallel::BatchStats;

pub use parallel::CacheAwareExplanationStore;

pub use parallel::CompressedBatch;

pub use parallel::HighPerformanceBatchProcessor;

pub use parallel::MemoryPool;

pub use parallel::ParallelConfig;

pub use parallel::ParallelExplanation;

pub use parallel::ParallelPermutationImportance;

pub use parallel::PermutationInput;

pub use parallel::ProgressCallback;

pub use parallel::StreamingBatchProcessor;

pub use partial_dependence::partial_dependence;

pub use permutation::permutation_importance;

pub use perturbation::analyze_robustness;

pub use perturbation::generate_perturbations;

pub use perturbation::PerturbationConfig;

pub use perturbation::PerturbationStrategy;

pub use plugins::ExampleCustomPlugin;

pub use plugins::ExecutionMetadata;

pub use plugins::ExecutionStatistics;

pub use plugins::ExplanationPlugin;

pub use plugins::InputType;

pub use plugins::LogLevel as PluginLogLevel;

pub use plugins::OutputType;

pub use plugins::PluginCapabilities;

pub use plugins::PluginCapabilityFilter;

pub use plugins::PluginConfig;

pub use plugins::PluginData;

pub use plugins::PluginExecution;

pub use plugins::PluginInput;

pub use plugins::PluginManager;

pub use plugins::PluginMetadata;

pub use plugins::PluginOutput;

pub use plugins::PluginOutputData;

pub use plugins::PluginParameter;

pub use plugins::PluginRegistry;

pub use plugins::PluginRegistryStatistics;

pub use probabilistic::bayesian_model_averaging;

pub use probabilistic::generate_bayesian_explanation;

pub use probabilistic::generate_probabilistic_counterfactuals;

pub use probabilistic::quantify_explanation_uncertainty;

pub use probabilistic::BayesianExplanationResult;

pub use probabilistic::BayesianModelAveragingResult;

pub use probabilistic::ProbabilisticConfig;

pub use probabilistic::ProbabilisticCounterfactualResult;

pub use probabilistic::UncertainExplanationResult;

pub use profiling::BottleneckType;

pub use profiling::HotPath;

pub use profiling::MethodProfile;

pub use profiling::OptimizationComplexity;

pub use profiling::OptimizationConfig;

pub use profiling::OptimizationOpportunity;

pub use profiling::OptimizationType;

pub use profiling::PerformanceBottleneck;

pub use profiling::ProfileGuidedOptimizer;

pub use profiling::RuntimeStatistics;

pub use profiling::Severity;

pub use quantum::CircuitComplexity;

pub use quantum::GateInstance;

pub use quantum::QuantumCircuit;

pub use quantum::QuantumExplainer;

pub use quantum::QuantumExplainerConfig;

pub use quantum::QuantumExplanation;

pub use quantum::QuantumGate;

pub use reporting::export_report;

pub use reporting::generate_quick_report;

pub use reporting::CaveatsAndRecommendations;

pub use reporting::DatasetInfo;

pub use reporting::EthicalConsiderations;

pub use reporting::EvaluationData;

pub use reporting::ExplanationSummary;

pub use reporting::Factor;

pub use reporting::IntendedUse;

pub use reporting::InterpretabilityReport;

pub use reporting::InterpretabilityScorecard;

pub use reporting::ModelCard;

pub use reporting::ModelDetails;

pub use reporting::OutputFormat;

pub use reporting::QuantitativeAnalysis;

pub use reporting::ReportConfig;

pub use reporting::ReportGenerator;

pub use reporting::ReportMetadata;

pub use reporting::ReportModelMetrics;

pub use reporting::TemplateStyle;

pub use reporting::TrainingData;

pub use rules::extract_rules_from_model;

pub use rules::generate_decision_rules;

pub use rules::generate_logical_explanations;

pub use rules::mine_association_rules;

pub use rules::simplify_rules;

pub use rules::AssociationRule;

pub use rules::ComparisonOperator;

pub use rules::DecisionRule;

pub use rules::RuleCondition;

pub use rules::RuleExtractionConfig;

pub use sensitivity::analyze_sensitivity;

pub use sensitivity::SensitivityConfig;

pub use sensitivity::SensitivityMethod;

pub use serialization::BatchSummary;

pub use serialization::CompressionType;

pub use serialization::DataStatistics;

pub use serialization::DatasetMetadata;

pub use serialization::ExplanationBatch;

pub use serialization::ExplanationConfiguration;

pub use serialization::ModelMetadata;

pub use serialization::SerializableExplanationResult;

pub use serialization::SerializationConfig;

pub use serialization::SerializationFormat;

pub use serialization::SerializationSummary;

pub use shapley::compute_deep_shap;

pub use shapley::compute_kernel_shap;

pub use shapley::compute_linear_shap;

pub use shapley::compute_partition_shap;

pub use shapley::compute_tree_shap;

pub use shapley::FeaturePartition;

pub use shapley::ShapleyConfig;

pub use shapley::ShapleyMetadata;

pub use shapley::ShapleyMethod;

pub use shapley::ShapleyResult;

pub use shapley::Tree;

pub use shapley::TreeNode;

pub use streaming::create_data_chunks;

pub use streaming::BackgroundStatistics;

pub use streaming::OnlineAggregator;

pub use streaming::StreamingConfig;

pub use streaming::StreamingDataIterator;

pub use streaming::StreamingExplainer;

pub use streaming::StreamingExplanationResult;

pub use streaming::StreamingShapExplainer;

pub use streaming::StreamingStatistics;

pub use testing::validate_explanation_output;

pub use testing::ConsistencyTestConfig;

pub use testing::FidelityTestConfig;

pub use testing::PropertyTestConfig;

pub use testing::PropertyTestResult;

pub use testing::PropertyViolation;

pub use testing::RobustnessTestConfig;

pub use testing::TestingSuite;

pub use time_series::AlignmentSegment;

pub use time_series::AlignmentType;

pub use time_series::DTWExplanation;

pub use time_series::DecompositionMethod;

pub use time_series::LagImportance;

pub use time_series::SeasonalDecomposition;

pub use time_series::TemporalImportance;

pub use time_series::TimeSeriesAnalyzer;

pub use time_series::TimeSeriesConfig;

pub use time_series::TrendAnalysis;

pub use time_series::TrendDirection;

pub use time_series::TrendSegment;

pub use uncertainty::analyze_prediction_uncertainty;

pub use uncertainty::calibrate_predictions;

pub use uncertainty::compute_calibration_metrics;

pub use uncertainty::quantify_uncertainty;

pub use uncertainty::CalibratedModel;

pub use uncertainty::CalibrationMethod;

pub use uncertainty::CalibrationMetrics;

pub use uncertainty::UncertaintyAnalysis;

pub use uncertainty::UncertaintyConfig;

pub use uncertainty::UncertaintyEstimator;

pub use uncertainty::UncertaintyResult;

pub use uncertainty::UncertaintyType;

pub use validation::AutomatedTestingResult;

pub use validation::CaseStudyMetadata;

pub use validation::CaseStudyValidationResult;

pub use validation::ConsistencyValidationResult;

pub use validation::DatasetValidationResult;

pub use validation::FeedbackSeverity;

pub use validation::HumanEvaluationResult;

pub use validation::MethodAgreement;

pub use validation::PerformanceBenchmark;

pub use validation::QualitativeFeedback;

pub use validation::StatisticalTest;

pub use validation::SyntheticValidationResult;

pub use validation::TestResult;

pub use validation::ValidationConfig;

pub use validation::ValidationFramework;

pub use visualization::create_3d_plot;

pub use visualization::create_3d_shap_plot;

pub use visualization::create_3d_surface_plot;

pub use visualization::create_comparative_plot;

pub use visualization::create_feature_importance_plot;

pub use visualization::create_partial_dependence_plot;

pub use visualization::create_shap_visualization;

pub use visualization::Animation3D;

pub use visualization::ColorScheme;

pub use visualization::ComparativePlot;

pub use visualization::ComparisonType;

pub use visualization::EasingType;

pub use visualization::FeatureImportancePlot;

pub use visualization::FeatureImportanceType;

pub use visualization::MobileConfig;

pub use visualization::PartialDependencePlot;

pub use visualization::Plot3D;

pub use visualization::Plot3DType;

pub use visualization::PlotConfig;

pub use visualization::ShapPlot;

pub use visualization::ShapPlotType;

pub use visualization::Surface3D;

pub use visualization_backend::AsciiBackend;

pub use visualization_backend::BackendCapabilities;

pub use visualization_backend::BackendConfig;

pub use visualization_backend::BackendRegistry;

pub use visualization_backend::ComparativeData;

pub use visualization_backend::CustomPlotData;

pub use visualization_backend::FeatureImportanceData;

pub use visualization_backend::HtmlBackend;

pub use visualization_backend::JsonBackend;

pub use visualization_backend::PartialDependenceData;

pub use visualization_backend::PlotType;

pub use visualization_backend::RenderedVisualization;

pub use visualization_backend::ShapData;

pub use visualization_backend::Theme;

pub use visualization_backend::VisualizationBackend;

pub use visualization_backend::VisualizationMetadata;

pub use visualization_backend::VisualizationRenderer;

pub use permutation::compute_score;

pub use types::*;

Modules

adversarial

Adversarial and Robustness Analysis Methods

anchors

Anchors explanations

attention

Attention and Activation Analysis

benchmarking

Benchmarking and Performance Analysis

builder

Builder pattern and fluent API for complex explanations

causal

Causal Analysis

complexity

Model complexity analysis

computer_vision

Computer Vision Interpretability Methods

counterfactual

Counterfactual explanations

dashboard

Dashboard Integration

deep_learning

Deep Learning Interpretability

distributed

Distributed computation infrastructure for enterprise-scale explanation tasks

enterprise

Enterprise features for model explanation and inspection

external_visualizations

External Visualization Library Integrations

fairness

Fairness and bias detection tools

federated

Federated Learning explanation methods with privacy preservation

framework

Trait-based explanation framework for composable strategies

gnn

Graph Neural Network (GNN) interpretability methods

gpu

GPU acceleration infrastructure for explanation methods

hooks

Explanation Hooks and Event Handling System

information_theoretic

Information-Theoretic Methods for Model Interpretability

lazy

Lazy evaluation system for expensive explanation computations

llm

Large Language Model (LLM) interpretability methods

local_explanations

Local Explanations for Model Inspection

memory

Memory management and caching for explanation algorithms

metrics_registry

Custom Explanation Metric Registration System

model_agnostic

Model-agnostic explanation methods

model_comparison

Model comparison and analysis tools

multimodal

Multi-modal model explanations for text, vision, and audio

nlp

Natural Language Processing Interpretability Methods

occlusion

Occlusion and Masking Methods

parallel

Parallel computation utilities for explanation methods

partial_dependence

Partial dependence plots

permutation

Permutation importance calculation

perturbation

Perturbation Strategies for Model Analysis

plugins

Plugin Architecture for Custom Explanation Methods

probabilistic

Probabilistic Explanations Module

profiling

Profile-guided optimization for explanation algorithms

quantum

Quantum Machine Learning interpretability methods

reporting

Report Generation Module

rules

Rule-based explanations and rule extraction

sensitivity

Sensitivity Analysis Methods

serialization

Serialization support for explanation results

shapley

Advanced Shapley value methods for model explanation

streaming

Streaming explanation computation for large datasets

testing

Comprehensive Testing Framework

time_series

Time Series Interpretability Module

types

Common types and enums for model inspection

uncertainty

Uncertainty Quantification

validation

Validation Framework for Explanation Quality Assessment

visualization

Comprehensive Visualization Framework for Machine Learning Model Inspection

visualization_backend

Extensible Visualization Backend System

Enums

SklearsError

Main error type for sklears

Functions

compute_feature_statistics

Utility function to compute feature statistics

create_feature_importance_data

Feature Importance Data

generate_feature_names

Utility function to generate feature names if not provided

validate_input_dimensions

Utility function to validate input dimensions

Type Aliases

Float

Default floating point type for the library

SklResult

Result type alias for sklears operations