evalml.pipelines.TimeSeriesClassificationPipeline.__init__¶
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TimeSeriesClassificationPipeline.__init__(parameters, random_seed=0)[source]¶ Machine learning pipeline for time series classification problems made out of transformers and a classifier.
- Required Class Variables:
component_graph (list): List of components in order. Accepts strings or ComponentBase subclasses in the list
- Parameters
parameters (dict) – Dictionary with component names as keys and dictionary of that component’s parameters as values. An empty dictionary {} implies using all default values for component parameters. Pipeline-level parameters such as gap and max_delay must be specified with the “pipeline” key. For example: Pipeline(parameters={“pipeline”: {“max_delay”: 4, “gap”: 2}}).
random_seed (int) – Seed for the random number generator. Defaults to 0.