evalml.pipelines.TimeSeriesBinaryClassificationPipeline¶
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class
evalml.pipelines.TimeSeriesBinaryClassificationPipeline(component_graph, parameters=None, custom_name=None, custom_hyperparameters=None, random_seed=0)[source]¶ Instance attributes
classes_Gets the class names for the problem.
custom_hyperparametersCustom hyperparameters for the pipeline.
custom_nameCustom name of the pipeline.
default_parametersThe default parameter dictionary for this pipeline.
feature_importanceImportance associated with each feature.
hyperparametersReturns hyperparameter ranges from all components as a dictionary
linearized_component_graphthis is not guaranteed to be in proper component computation order
model_familyReturns model family of this pipeline template
nameName of the pipeline.
parametersParameter dictionary for this pipeline
problem_typesummaryA short summary of the pipeline structure, describing the list of components used.
thresholdThreshold used to make a prediction.
Methods:
Machine learning pipeline for time series classification problems made out of transformers and a classifier.
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
Fit a time series classification pipeline.
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 current and additional objectives.
Class Inheritance¶
