evalml.pipelines.TimeSeriesBaselineRegressionPipeline

class evalml.pipelines.TimeSeriesBaselineRegressionPipeline(parameters, random_state=None, random_seed=0)[source]

Baseline Pipeline for time series regression problems.

name = 'Time Series Baseline Regression Pipeline'
custom_name = None
summary = 'Time Series Baseline Estimator'
component_graph = ['Time Series Baseline Estimator']
problem_type = 'time series regression'
model_family = 'baseline'
hyperparameters = {'Time Series Baseline Estimator': {}}
custom_hyperparameters = None
default_parameters = {'Time Series Baseline Estimator': {'gap': 1}}

Instance attributes

feature_importance

Return importance associated with each feature.

linearized_component_graph

parameters

Returns parameter dictionary for this pipeline

Methods:

__init__

Machine learning pipeline for time series regression problems made out of transformers and a classifier.

clone

Constructs a new pipeline with the same components, parameters, and random state.

compute_estimator_features

Transforms the data by applying all pre-processing components.

describe

Outputs pipeline details including component parameters

fit

Fit a time series regression pipeline.

get_component

Returns component by name

graph

Generate an image representing the pipeline graph

graph_feature_importance

Generate a bar graph of the pipeline’s feature importance

load

Loads pipeline at file path

predict

Make predictions using selected features.

save

Saves pipeline at file path

score

Evaluate model performance on current and additional objectives.

Class Inheritance

Inheritance diagram of TimeSeriesBaselineRegressionPipeline