evalml.pipelines.TimeSeriesMulticlassClassificationPipeline

class evalml.pipelines.TimeSeriesMulticlassClassificationPipeline(parameters, random_state=None, random_seed=0)[source]
name = 'Time Series Multiclass Classification Pipeline'
custom_name = None
problem_type = 'time series multiclass'

Instance attributes

classes_

Gets the class names for the problem.

feature_importance

Return importance associated with each feature.

parameters

Returns parameter dictionary for this pipeline

Methods:

__init__

Machine learning pipeline for time series classification 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 classification 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.

predict_proba

Make probability estimates for labels.

save

Saves pipeline at file path

score

Evaluate model performance on current and additional objectives.

Class Inheritance

Inheritance diagram of TimeSeriesMulticlassClassificationPipeline