Base

systematica.portfolio.trial_selectors.base

BaseTrialSelector

BaseTrialSelector(
    name=None,
)

Abstract class for hyperparameter selection.

This is the base class that defines the interface for all parameter selectors. Child classes must implement the run method.

Method generated by attrs for class BaseTrialSelector.

Ancestors

• abc.ABC

Descendants

• systematica.portfolio.trial_selectors.models.AUCMaximization
• systematica.portfolio.trial_selectors.models.BestMetricPoint
• systematica.portfolio.trial_selectors.models.ClosestIdealPoint
• systematica.portfolio.trial_selectors.models.DiversitySampling
• systematica.portfolio.trial_selectors.models.EfficientFrontierProjection
• systematica.portfolio.trial_selectors.models.ElbowPoint
• systematica.portfolio.trial_selectors.models.EpsilonConstraint
• systematica.portfolio.trial_selectors.models.HullExtremePoint
• systematica.portfolio.trial_selectors.models.HullMidPoint
• systematica.portfolio.trial_selectors.models.HullPoint
• systematica.portfolio.trial_selectors.models.HypervolumeContribution
• systematica.portfolio.trial_selectors.models.MaxMetricPoint
• systematica.portfolio.trial_selectors.models.MinMetricPoint
• systematica.portfolio.trial_selectors.models.Preference
• systematica.portfolio.trial_selectors.models.Random
• systematica.portfolio.trial_selectors.models.RegretMinimization
• systematica.portfolio.trial_selectors.models.RiskAwareUtility

Instance variables

• name: Name of the selector, used for identification.

Methods

run

run(
    self,
    df: pandas.core.frame.DataFrame,
) ‑> pandas.core.series.Series | pandas.core.frame.DataFrame

Execute the selection algorithm.

Parameters:

Name	Type	Default	Description
df	pandas.DataFrame	--	DataFrame containing parameters to select from.

Returns:

Type	Description
pd.Series or pd.DataFrame	The selected parameters or None if no parameters can be selected.

WrapTrialSelectors

WrapTrialSelectors(
    strategies: List[systematica.portfolio.trial_selectors.base.BaseTrialSelector],
)

Wrapper for parameter selectors.

This class allows multiple selection strategies to be run on the same data.

Method generated by attrs for class WrapTrialSelectors.

Instance variables

• strategies: List[systematica.portfolio.trial_selectors.base.BaseTrialSelector]: List of selector strategies to apply.

Methods

run_all

run_all(
    self,
    df: pandas.core.frame.DataFrame,
) ‑> dict

Run all selector strategies on the provided data.

Parameters:

Name	Type	Default	Description
df	pandas.DataFrame	--	Data to run the strategies on.

Returns:

Type	Description
dict	Dictionary mapping strategy names to selection results.