lir.lrsystems.score_based module

class lir.lrsystems.score_based.ScoreBasedSystem(preprocessing_pipeline: Transformer | None, pairing_function: PairingMethod, evaluation_pipeline: Transformer | None)[source]

Bases: LRSystem

Provide a representation of a common source, score-based LR system.

In this strategy, it is possible to prepare the data within a preprocessing_pipeline, create corresponding pairs of instances using the pairing_function and subsequently calculate scores as well as transform these scores to LLR’s in the final evaluation_pipeline.

Parameters:

  • preprocessing_pipeline (Transformer | None) – Pipeline that preprocesses instances before pairing and evaluation.

  • pairing_function (PairingMethod) – Pairing method used to construct trace/reference comparisons.

  • evaluation_pipeline (Transformer | None) – Pipeline that converts scores to likelihood-ratio outputs.

apply(instances: InstanceData) → LLRData[source]

Use LR system to calculate LLR data from the instances.

Applies the score-based LR system on a set of instances, optionally with corresponding labels, and returns a representation of the calculated LLR data through the LLRData tuple.

The system takes instances as input, and calculates LLRs for pairs of instances. That means that there is a 2-1 relation between input and output data.

Parameters:

instances (InstanceData) – Input instances to be processed by this method.

Returns:

Likelihood-ratio data produced by applying the LR system.

Return type:

LLRData

fit(instances: InstanceData) → Self[source]

Fit the model on the instance data.

Parameters:

instances (InstanceData) – Input instances to be processed by this method.

Returns:

This LR system instance after fitting the evaluation pipeline.

Return type:

Self