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BayBE documentation

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Readme
User Guide
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Examples
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- Basics
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  - Campaign
  - Recommenders
- Searchspaces
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- Constraints Discrete
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- Constraints Continuous
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  - Hybrid Space
  - Linear
- Multi Target
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  - Desirability
  - Pareto
- Serialization
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- Custom Surrogates
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  - Custom Pretrained
  - Surrogate Params
- Mixtures
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  - Slot Based
  - Traditional
- Backtesting
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- Multi Armed Bandit
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  - Bernoulli Multi Armed Bandit
- Transfer Learning
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  - Basic Transfer Learning
  - Backtesting
- Custom Hooks
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FAQ

baybe
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- baybe.acquisition
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  - baybe.acquisition.acqfs
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  - baybe.acquisition.base
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    - AcquisitionFunction
  - baybe.acquisition.partial
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    - PartialAcquisitionFunction
  - baybe.acquisition.utils
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    - baybe.acquisition.utils.convert_acqf
    - baybe.acquisition.utils.str_to_acqf
- baybe.campaign
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  - Campaign
- baybe.constraints
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  - baybe.constraints.base
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  - baybe.constraints.conditions
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  - baybe.constraints.continuous
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    - ContinuousCardinalityConstraint
    - ContinuousLinearConstraint
  - baybe.constraints.deprecation
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  - baybe.constraints.discrete
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  - baybe.constraints.utils
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    - baybe.constraints.utils.is_cardinality_fulfilled
  - baybe.constraints.validation
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- baybe.exceptions
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- baybe.insights
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  - baybe.insights.shap
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- baybe.kernels
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  - baybe.kernels.base
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  - baybe.kernels.composite
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- baybe.objectives
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  - baybe.objectives.base
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    - baybe.objectives.base.to_objective
    - Objective
  - baybe.objectives.desirability
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    - baybe.objectives.desirability.scalarize
    - DesirabilityObjective
  - baybe.objectives.enum
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    - Scalarizer
  - baybe.objectives.pareto
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    - ParetoObjective
  - baybe.objectives.single
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    - SingleTargetObjective
  - baybe.objectives.validation
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    - baybe.objectives.validation.validate_target_names
- baybe.parameters
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  - baybe.parameters.base
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  - baybe.parameters.categorical
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    - CategoricalParameter
    - TaskParameter
  - baybe.parameters.custom
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    - CustomDiscreteParameter
  - baybe.parameters.enum
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  - baybe.parameters.numerical
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    - NumericalContinuousParameter
    - NumericalDiscreteParameter
  - baybe.parameters.substance
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    - baybe.parameters.substance.Smiles
    - SubstanceParameter
  - baybe.parameters.utils
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  - baybe.parameters.validation
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- baybe.priors
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  - baybe.priors.base
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    - Prior
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- baybe.recommenders
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  - baybe.recommenders.base
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    - RecommenderProtocol
  - baybe.recommenders.meta
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    - baybe.recommenders.meta.base
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      - MetaRecommender
    - baybe.recommenders.meta.sequential
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  - baybe.recommenders.naive
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    - NaiveHybridSpaceRecommender
  - baybe.recommenders.pure
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    - baybe.recommenders.pure.base
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      - PureRecommender
    - baybe.recommenders.pure.bayesian
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      - baybe.recommenders.pure.bayesian.base
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        BayesianRecommender
      - baybe.recommenders.pure.bayesian.botorch
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        BotorchRecommender
      - baybe.recommenders.pure.bayesian.sequential_greedy
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        baybe.recommenders.pure.bayesian.sequential_greedy.SequentialGreedyRecommender
    - baybe.recommenders.pure.nonpredictive
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      - baybe.recommenders.pure.nonpredictive.base
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        NonPredictiveRecommender
      - baybe.recommenders.pure.nonpredictive.clustering
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        GaussianMixtureClusteringRecommender
        
        KMeansClusteringRecommender
        
        PAMClusteringRecommender
        
        SKLearnClusteringRecommender
      - baybe.recommenders.pure.nonpredictive.sampling
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        FPSRecommender
        
        RandomRecommender
- baybe.searchspace
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  - baybe.searchspace.continuous
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    - SubspaceContinuous
  - baybe.searchspace.core
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  - baybe.searchspace.discrete
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  - baybe.searchspace.validation
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- baybe.serialization
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  - baybe.serialization.core
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  - baybe.serialization.mixin
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    - SerialMixin
  - baybe.serialization.utils
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    - baybe.serialization.utils.deserialize_dataframe
    - baybe.serialization.utils.serialize_dataframe
- baybe.simulation
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  - baybe.simulation.core
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    - baybe.simulation.core.simulate_experiment
  - baybe.simulation.lookup
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    - baybe.simulation.lookup.look_up_targets
  - baybe.simulation.scenarios
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    - baybe.simulation.scenarios.simulate_scenarios
  - baybe.simulation.transfer_learning
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    - baybe.simulation.transfer_learning.simulate_transfer_learning
- baybe.surrogates
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  - baybe.surrogates.bandit
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    - BetaBernoulliMultiArmedBanditSurrogate
  - baybe.surrogates.base
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  - baybe.surrogates.composite
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    - CompositeSurrogate
  - baybe.surrogates.custom
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    - baybe.surrogates.custom.register_custom_architecture
    - CustomONNXSurrogate
  - baybe.surrogates.gaussian_process
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    - baybe.surrogates.gaussian_process.core
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      - GaussianProcessSurrogate
    - baybe.surrogates.gaussian_process.kernel_factory
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    - baybe.surrogates.gaussian_process.presets
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        baybe.surrogates.gaussian_process.presets.core.make_gp_from_preset
        
        GaussianProcessPreset
      - baybe.surrogates.gaussian_process.presets.default
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        DefaultKernelFactory
      - baybe.surrogates.gaussian_process.presets.edbo
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        EDBOKernelFactory
  - baybe.surrogates.linear
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    - BayesianLinearSurrogate
  - baybe.surrogates.naive
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    - MeanPredictionSurrogate
  - baybe.surrogates.ngboost
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    - NGBoostSurrogate
  - baybe.surrogates.random_forest
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    - RandomForestSurrogate
  - baybe.surrogates.utils
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  - baybe.surrogates.validation
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    - baybe.surrogates.validation.get_model_params_validator
    - baybe.surrogates.validation.validate_custom_architecture_cls
- baybe.targets
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  - baybe.targets.base
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    - Target
  - baybe.targets.binary
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    - baybe.targets.binary.ChoiceValue
    - BinaryTarget
  - baybe.targets.enum
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    - TargetMode
    - TargetTransformation
  - baybe.targets.numerical
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    - NumericalTarget
  - baybe.targets.transforms
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- baybe.telemetry
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- baybe.utils
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  - baybe.utils.augmentation
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    - baybe.utils.augmentation.df_apply_dependency_augmentation
    - baybe.utils.augmentation.df_apply_permutation_augmentation
  - baybe.utils.basic
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  - baybe.utils.boolean
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  - baybe.utils.chemistry
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  - baybe.utils.clustering_algorithms
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    - baybe.utils.clustering_algorithms.third_party
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      - baybe.utils.clustering_algorithms.third_party.kmedoids
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        KMedoids
  - baybe.utils.conversion
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  - baybe.utils.dataframe
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  - baybe.utils.interval
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  - baybe.utils.memory
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    - baybe.utils.memory.bytes_to_human_readable
  - baybe.utils.numerical
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  - baybe.utils.random
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    - baybe.utils.random.set_random_seed
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  - baybe.utils.sampling_algorithms
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  - baybe.utils.scaling
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    - ColumnTransformer
  - baybe.utils.torch
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    - baybe.utils.torch.VARNAME_TORCH_USE_SINGLE_PRECISION
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  - baybe.utils.validation
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Misc

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Backtesting¶

These examples demonstrate BayBE’s Backtesting capabilities.

Custom Blackbox
Impute Mode
Full Initial Data
Full Lookup

Optimizing a Custom Black-Box Function

Modeling a Mixture in Traditional Representation

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