MulticlassClassificationPipeline(component_graph, parameters=None, custom_name=None, random_seed=0)¶
Pipeline subclass for all multiclass classification pipelines.
Gets the class names for the problem.
Custom name of the pipeline.
Importance associated with each feature.
this is not guaranteed to be in proper component computation order
Returns model family of this pipeline template
Name of the pipeline.
Parameter dictionary for this pipeline
A short summary of the pipeline structure, describing the list of components used.
Machine learning pipeline made out of transformers and a estimator.
Determine whether the threshold of a binary classification pipeline can be tuned.
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
Apply component inverse_transform methods to estimator predictions in reverse order.
Loads pipeline at file path
Constructs a new instance of the pipeline with the same component graph but with a different set of parameters.
Make predictions using selected features.
Make probability estimates for labels.
Saves pipeline at file path
Evaluate model performance on objectives