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MrSEQL

API referenceSource

MrSEQL = Multiple Representations Sequence Learning classification model.

Quickstart

python
from sktime.classification.shapelet_based import MrSEQL

estimator = MrSEQL(seql_mode='fs', symrep='sax', custom_config=None)

Parameters(3)

seql_modestr, either ‘clf’ or ‘fs’ (default).
In the ‘clf’ mode, Mr-SEQL is an ensemble of SEQL models, while in the ‘fs’ mode Mr-SEQL, trains a logistic regression model with features extracted by SEQL from symbolic representations of time series.
symrepstr, or list or tuple of string, strings being ‘sax’ or ‘sfa’.
default = “sax”, i.e., only SAX features, no SFA features. The symbolic representations to be used to transform the input time series.
custom_configdict, optional, default=None
Customized parameters for the symbolic transformation. If defined, symrep will be ignored. (no documentation of this parameter is provided in the original mrseql code)

References

  1. [1 ] Thach Le Nguyen, Severin Gsponer, Iulia Ilie, Martin O’Reilly, Georgiana Ifrim. “Interpretable Time Series Classification Using Linear Models and Multi-resolution Multi-domain Symbolic Representations”, Data Mining and Knowledge Discovery, 2019.