Pipeline subclass for all binary classification pipelines.
Gets the class names for the problem.
Return importance associated with each feature.
Returns parameter dictionary for this pipeline
Threshold used to make a prediction.
Machine learning classification pipeline made out of transformers and a classifier.
Constructs a new pipeline with the same components, parameters, and random state.
Transforms the data by applying all pre-processing components.
Outputs pipeline details including component parameters
Build a classification model. For string and categorical targets, classes are sorted
Returns component by name
Generate an image representing the pipeline graph
Generate a bar graph of the pipeline’s feature importance
Loads pipeline at file path
Make predictions using selected features.
Make probability estimates for labels.
Saves pipeline at file path
Evaluate model performance on objectives