evalml.pipelines.BinaryClassificationPipeline¶
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class
evalml.pipelines.
BinaryClassificationPipeline
(component_graph, parameters=None, custom_name=None, custom_hyperparameters=None, random_seed=0)[source]¶ Pipeline subclass for all binary classification pipelines.
Instance attributes
classes_
Gets the class names for the problem.
custom_hyperparameters
Custom hyperparameters for the pipeline.
custom_name
Custom name of the pipeline.
default_parameters
The default parameter dictionary for this pipeline.
feature_importance
Importance associated with each feature.
hyperparameters
Returns hyperparameter ranges from all components as a dictionary
linearized_component_graph
this is not guaranteed to be in proper component computation order
model_family
Returns model family of this pipeline template
name
Name of the pipeline.
parameters
Parameter dictionary for this pipeline
problem_type
summary
A short summary of the pipeline structure, describing the list of components used.
threshold
Threshold used to make a prediction.
Methods:
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
Loads pipeline at file path
Constructs a new instance of the pipeline with the same component graph but with a different set of parameters.
Optimize the pipeline threshold given the objective to use.
Make predictions using selected features.
Make probability estimates for labels.
Saves pipeline at file path
Evaluate model performance on objectives