Expand description
Gaussian mixture models
This module provides Gaussian mixture models for clustering and density estimation, including standard EM-based GMM and Bayesian variants that can automatically determine the number of components.
Re-exports§
pub use common::CovarianceMatrices;pub use common::CovarianceType;pub use common::InitMethod;pub use common::ModelSelection;pub use gaussian::GaussianMixture;pub use gaussian::GaussianMixtureTrained;pub use variational::VariationalBayesianGMM;pub use variational::VariationalBayesianGMMTrained;pub use mean_field_variational::MeanFieldVariationalGMM;pub use mean_field_variational::MeanFieldVariationalGMMTrained;pub use stochastic_variational::OptimizerType;pub use stochastic_variational::StochasticVariationalGMM;pub use stochastic_variational::StochasticVariationalGMMTrained;pub use structured_variational::StructuredFamily;pub use structured_variational::StructuredVariationalGMM;pub use structured_variational::StructuredVariationalGMMTrained;pub use advi::ADBackend;pub use advi::ADVIGaussianMixture;pub use advi::ADVIGaussianMixtureTrained;pub use advi::ADVIOptimizer;pub use advi::Dual;pub use empirical_bayes::EmpiricalBayesGMM;pub use empirical_bayes::EmpiricalBayesGMMTrained;pub use empirical_bayes::EmpiricalBayesMethod;pub use empirical_bayes::HyperparameterState;pub use prior_sensitivity::GridSearchResult;pub use prior_sensitivity::InfluenceScore;pub use prior_sensitivity::ParameterVariances;pub use prior_sensitivity::PerturbationResult;pub use prior_sensitivity::PriorSensitivityAnalyzer;pub use prior_sensitivity::SensitivityAnalysisResult;pub use prior_sensitivity::SensitivitySummary;pub use prior_elicitation::ConstraintType;pub use prior_elicitation::DomainConstraint;pub use prior_elicitation::ElicitationAnswer;pub use prior_elicitation::ElicitationMethod;pub use prior_elicitation::ElicitationQuestion;pub use prior_elicitation::ElicitationResult;pub use prior_elicitation::PriorElicitationEngine;pub use prior_elicitation::PriorQualityMetrics;pub use prior_elicitation::PriorSpecification;pub use prior_elicitation::QuestionType;pub use nuts::NUTSResult;pub use nuts::NUTSSampler;pub use bayesian::BayesianGaussianMixture;pub use bayesian::BayesianGaussianMixtureTrained;pub use robust::RobustGaussianMixture;pub use robust::RobustGaussianMixtureTrained;pub use online::OnlineGaussianMixture;pub use online::OnlineGaussianMixtureTrained;pub use student_t::StudentTMixture;pub use student_t::StudentTMixtureTrained;pub use exponential_family::ExponentialFamilyMixture;pub use exponential_family::ExponentialFamilyMixtureTrained;pub use exponential_family::ExponentialFamilyType;pub use von_mises_fisher::VonMisesFisher;pub use von_mises_fisher::VonMisesFisherMixture;pub use von_mises_fisher::VonMisesFisherMixtureFitted;pub use time_series::DynamicMixture;pub use time_series::DynamicMixtureBuilder;pub use time_series::DynamicMixtureTrained;pub use time_series::HMMConfig;pub use time_series::HMMError;pub use time_series::HiddenMarkovModel;pub use time_series::HiddenMarkovModelBuilder;pub use time_series::HiddenMarkovModelTrained;pub use time_series::ParameterEvolution;pub use time_series::RSMConfig;pub use time_series::RegimeParameters;pub use time_series::RegimeSwitchingModel;pub use time_series::RegimeSwitchingModelBuilder;pub use time_series::RegimeSwitchingModelTrained;pub use time_series::RegimeType;pub use time_series::SSMConfig;pub use time_series::SwitchingStateSpaceModel;pub use time_series::SwitchingStateSpaceModelBuilder;pub use time_series::SwitchingStateSpaceModelTrained;pub use time_series::TemporalGaussianMixture;pub use time_series::TemporalGaussianMixtureBuilder;pub use time_series::TemporalGaussianMixtureTrained;pub use nonparametric::ChineseRestaurantProcess;pub use nonparametric::ChineseRestaurantProcessTrained;pub use nonparametric::DirichletProcessGaussianMixture;pub use nonparametric::DirichletProcessGaussianMixtureTrained;pub use spatial::GearysC;pub use spatial::GeographicMixture;pub use spatial::GeographicMixtureBuilder;pub use spatial::GeographicMixtureTrained;pub use spatial::LocalIndicators;pub use spatial::MarkovRandomFieldMixture;pub use spatial::MarkovRandomFieldMixtureBuilder;pub use spatial::MarkovRandomFieldMixtureTrained;pub use spatial::MoransI;pub use spatial::SpatialAutocorrelationAnalyzer;pub use spatial::SpatialClusteringQuality;pub use spatial::SpatialConstraint;pub use spatial::SpatiallyConstrainedGMM;pub use spatial::SpatiallyConstrainedGMMBuilder;pub use spatial::SpatiallyConstrainedGMMTrained;pub use multi_modal::FusionStrategy;pub use multi_modal::ModalitySpec;pub use multi_modal::MultiModalConfig;pub use multi_modal::MultiModalGaussianMixture;pub use multi_modal::MultiModalGaussianMixtureBuilder;pub use multi_modal::MultiModalGaussianMixtureTrained;pub use robust_methods::BreakdownAnalysis;pub use robust_methods::InfluenceDiagnostics;pub use robust_methods::MEstimatorGMM;pub use robust_methods::MEstimatorGMMBuilder;pub use robust_methods::MEstimatorGMMTrained;pub use robust_methods::MEstimatorType;pub use robust_methods::TrimmedLikelihoodConfig;pub use regularization::ElasticNetGMM;pub use regularization::ElasticNetGMMBuilder;pub use regularization::ElasticNetGMMTrained;pub use regularization::GroupLassoGMM;pub use regularization::GroupLassoGMMBuilder;pub use regularization::GroupLassoGMMTrained;pub use regularization::L1RegularizedGMM;pub use regularization::L1RegularizedGMMBuilder;pub use regularization::L1RegularizedGMMTrained;pub use regularization::L2RegularizedGMM;pub use regularization::L2RegularizedGMMBuilder;pub use regularization::L2RegularizedGMMTrained;pub use regularization::RegularizationType;pub use optimization_enhancements::AcceleratedEM;pub use optimization_enhancements::AcceleratedEMBuilder;pub use optimization_enhancements::AcceleratedEMTrained;pub use optimization_enhancements::AccelerationType;pub use optimization_enhancements::NaturalGradientGMM;pub use optimization_enhancements::NaturalGradientGMMBuilder;pub use optimization_enhancements::NaturalGradientGMMTrained;pub use optimization_enhancements::QuasiNewtonGMM;pub use optimization_enhancements::QuasiNewtonGMMBuilder;pub use optimization_enhancements::QuasiNewtonGMMTrained;pub use optimization_enhancements::QuasiNewtonMethod;pub use adaptive_streaming::AdaptiveStreamingConfig;pub use adaptive_streaming::AdaptiveStreamingGMM;pub use adaptive_streaming::AdaptiveStreamingGMMBuilder;pub use adaptive_streaming::AdaptiveStreamingGMMTrained;pub use adaptive_streaming::CreationCriterion;pub use adaptive_streaming::DeletionCriterion;pub use adaptive_streaming::DriftDetectionMethod;pub use large_scale::BatchStrategy;pub use large_scale::MiniBatchGMM;pub use large_scale::MiniBatchGMMBuilder;pub use large_scale::MiniBatchGMMTrained;pub use large_scale::ParallelGMM;pub use large_scale::ParallelGMMBuilder;pub use large_scale::ParallelGMMTrained;pub use large_scale::ParallelStrategy;pub use approximation::ImportanceSamplingGMM;pub use approximation::ImportanceSamplingGMMBuilder;pub use approximation::ImportanceSamplingGMMTrained;pub use approximation::ImportanceSamplingStrategy;pub use approximation::LaplaceGMM;pub use approximation::LaplaceGMMBuilder;pub use approximation::LaplaceGMMTrained;pub use approximation::MonteCarloGMM;pub use approximation::MonteCarloGMMBuilder;pub use approximation::MonteCarloGMMTrained;pub use approximation::MonteCarloMethod;
Modules§
- adaptive_
streaming - Adaptive Streaming Mixture Models
- advi
- Auto-generated module structure
- approximation
- Approximation Methods for Mixture Models
- bayesian
- Bayesian Gaussian Mixture Models
- common
- Common utilities for mixture models
- empirical_
bayes - Empirical Bayes Methods for Mixture Models
- exponential_
family - Exponential Family Mixture Models
- gaussian
- Standard Gaussian Mixture Models
- large_
scale - Large-Scale Mixture Model Methods
- mean_
field_ variational - Mean-Field Variational Inference for Mixture Models
- multi_
modal - Multi-Modal Data Mixture Models
- nonparametric
- Nonparametric Mixture Models
- nuts
- No-U-Turn Sampler (NUTS) for Bayesian Mixture Models
- online
- Online Gaussian Mixture Models
- optimization_
enhancements - Optimization Enhancements for Mixture Models
- prior_
elicitation - Prior Elicitation Tools for Gaussian Mixture Models
- prior_
sensitivity - Prior Sensitivity Analysis for Mixture Models
- regularization
- Regularization Techniques for Mixture Models
- robust
- Robust Gaussian Mixture Models
- robust_
methods - Advanced Robust Methods for Mixture Models
- spatial
- Spatial Mixture Models Module
- stochastic_
variational - Stochastic Variational Inference for Large-Scale Mixture Models
- structured_
variational - Structured Variational Approximations for Gaussian Mixture Models
- student_
t - Student-t Mixture Models
- time_
series - Time Series Mixture Models
- variational
- Variational Bayesian Gaussian Mixture Models
- von_
mises_ fisher - Von Mises-Fisher Mixture Models