voiage.metamodels
Metamodels for Value of Information analysis.
Classes
Section titled “Classes”- Metamodel A protocol for metamodels used in VOI analysis.
- MLP A simple MLP model.
- FlaxMetamodel A metamodel that uses a Flax MLP to predict the target values.
- TinyGPMetamodel A metamodel that uses a tinygp GP to predict the target values.
- RandomForestMetamodel A metamodel that uses a Random Forest to predict the target values.
- GAMMetamodel A metamodel that uses a Generalized Additive Model to predict the target values.
- BARTMetamodel A metamodel that uses a BART (Bayesian Additive Regression Trees) to predict the target values.
- ActiveLearningMetamodel A metamodel that uses active learning to iteratively improve its predictions.
- EnsembleMetamodel A metamodel that combines predictions from multiple metamodels.
- PyTorchNNMetamodel A metamodel that uses a PyTorch neural network to predict the target values.
Functions
Section titled “Functions”- calculate_diagnostics Calculate comprehensive diagnostics for a fitted metamodel.
- cross_validate Perform cross-validation for a metamodel.
- compare_metamodels Compare multiple metamodels using cross-validation.