biofefi.pages package¶
Submodules¶
biofefi.pages.1_New_Experiment module¶
biofefi.pages.2_Data_Preprocessing module¶
- biofefi.pages.2_Data_Preprocessing.build_config() PreprocessingOptions¶
Build the configuration object for preprocessing.
biofefi.pages.3_Data_Visualisation module¶
biofefi.pages.4_Train_Models module¶
- biofefi.pages.4_Train_Models.build_configuration() tuple[MachineLearningOptions, ExecutionOptions, PlottingOptions, str]¶
Build the configuration options to run the Machine Learning pipeline.
- Returns:
The machine learning options, general execution options, plotting options, experiment name
- Return type:
tuple[MachineLearningOptions, ExecutionOptions, PlottingOptions, str]
- biofefi.pages.4_Train_Models.pipeline(ml_opts: MachineLearningOptions, exec_opts: ExecutionOptions, plotting_opts: PlottingOptions, experiment_name: str)¶
This function actually performs the steps of the pipeline. It can be wrapped in a process it doesn’t block the UI.
- Parameters:
ml_opts (MachineLearningOptions) – Options for machine learning.
exec_opts (ExecutionOptions) – General execution options.
plotting_opts (PlottingOptions) – Options for plotting.
experiment_name (str) – The name of the experiment.
biofefi.pages.5_Feature_Importance module¶
- biofefi.pages.5_Feature_Importance.build_configuration() tuple[FuzzyOptions | None, FeatureImportanceOptions, ExecutionOptions, str, list]¶
Build the configuration objects for the pipeline.
- Returns:
- tuple[
FuzzyOptions | None, FeatureImportanceOptions, ExecutionOptions, str, list
]: The configuration for fuzzy, FI and ML pipelines, the experiment name and the list of models to explain.
- biofefi.pages.5_Feature_Importance.pipeline(fuzzy_opts: FuzzyOptions, fi_opts: FeatureImportanceOptions, exec_opts: ExecutionOptions, plot_opts: PlottingOptions, experiment_name: str, explain_models: list)¶
This function actually performs the steps of the pipeline. It can be wrapped in a process it doesn’t block the UI.
- Parameters:
fuzzy_opts (FuzzyOptions) – Options for fuzzy feature importance.
fi_opts (FeatureImportanceOptions) – Options for feature importance.
exec_opts (ExecutionOptions) – Options for pipeline execution.
plot_opts (PlottingOptions) – Options for plotting.
experiment_name (str) – The experiment name.
explain_models (list) – The models to analyse.