Table of Contents

Namespace AiDotNet.AutoML

Classes

ArchitectureDto

Data transfer object for architecture JSON serialization.

Architecture<T>

Represents a neural network architecture discovered through NAS.

AutoMLEnsembleModel<T>

A simple tabular ensemble model used as a facade-safe AutoML final model.

AutoMLModelBase<T, TInput, TOutput>

Base class for AutoML models that automatically search for optimal model configurations

BayesianOptimizationAutoML<T, TInput, TOutput>

Built-in AutoML strategy that uses a lightweight Bayesian-style surrogate to guide trial selection.

BuiltInSupervisedAutoMLModelBase<T, TInput, TOutput>

Base class for built-in supervised AutoML strategies that operate on tabular Matrix/Vector tasks.

CompressionOptimizerOptions

Configuration options for the compression optimizer.

CompressionOptimizer<T>

Automatically finds the best compression configuration for a model.

CompressionTrial<T>

Represents a compression configuration to be evaluated.

DiffusionAutoML<T>

AutoML for diffusion models with automatic hyperparameter optimization.

DiffusionTrialConfig<T>

Configuration for a diffusion model trial in AutoML.

EvolutionaryAutoML<T, TInput, TOutput>

Built-in AutoML strategy that uses an evolutionary (genetic) approach to propose new trials.

MultiFidelityAutoML<T, TInput, TOutput>

Built-in AutoML strategy that uses multi-fidelity (successive halving) and ASHA scheduling.

NeuralArchitectureSearch<T>

Neural Architecture Search implementation with gradient-based (DARTS) support

OperationDto

Data transfer object for a single operation in the architecture.

ParameterRange

Defines the range and type of a hyperparameter for AutoML search

RandomSearchAutoML<T, TInput, TOutput>

AutoML implementation that uses random search over candidate model types and hyperparameters.

SearchConstraint

Defines a constraint for AutoML search to limit the search space or enforce requirements.

SupervisedAutoMLModelBase<T, TInput, TOutput>

Base class for AutoML implementations that train and score supervised models.

TrialResult

Represents the result of a single trial during AutoML search.

Enums

ConstraintType

Defines the types of constraints that can be applied to AutoML search.

DiffusionSchedulerType

Represents the type of scheduler for diffusion sampling.

NoisePredictorType

Represents the type of noise predictor architecture.