lir package
LiR - Toolkit for developing, optimising and evaluating Likelihood Ratio (LR) systems.
This allows benchmarking of LR systems on different datasets, investigating impact of different sampling schemes or techniques, and doing case-based validation and computation of case LRs.
- lir.is_interactive() bool[source]
Determine if the LiR tool is running from the CLI and should be interactive.
This method is used, for example, to determine if a progress bar should be shown.
- Returns:
True when standard output is connected to a terminal, otherwise False.
- Return type:
bool
Subpackages
- lir.algorithms package
- Submodules
- lir.algorithms.bayeserror module
- lir.algorithms.bootstraps module
- lir.algorithms.devpav module
- lir.algorithms.invariance_bounds module
- lir.algorithms.isotonic_regression module
- lir.algorithms.kde module
- lir.algorithms.llr_overestimation module
- lir.algorithms.logistic_regression module
- lir.algorithms.mcmc module
- lir.algorithms.percentile_rank module
- Submodules
- lir.config package
- Submodules
- lir.data package
- lir.datasets package
- lir.experiments package
- lir.lrsystems package
- lir.metrics package
- lir.plotting package
- lir.resources package
- lir.transform package
BinaryClassifierTransformerCsvWriterDataWriterFunctionTransformerIdentityNumpyTransformerSKLearnPipelineModuleSklearnTransformerSklearnTransformerTypeTeeTransformerTransformerWrapperas_transformer()- Submodules
Submodules
- lir.aggregation module
- lir.bounding module
- lir.data_strategies module
- lir.main module
- lir.persistence module
- lir.registry module
- lir.util module