On the Usage and Performance of the Hierarchical Vote Collective of Transformation-Based Ensembles Version 1.0 (HIVE-COTE v1.0)

Bagnall, Tony, Flynn, Michael, Large, James and Middlehurst, Matthew (2020) On the Usage and Performance of the Hierarchical Vote Collective of Transformation-Based Ensembles Version 1.0 (HIVE-COTE v1.0). In: Lecture Notes in Computer Science. Springer, pp. 3-18. ISBN 978-3-030-65741-3

Full text not available from this repository. (Request a copy)

Abstract

The Hierarchical Vote Collective of Transformation-based Ensembles (HIVE-COTE) is a heterogeneous meta ensemble for time series classification. Since it was first proposed in 2016, the algorithm has undergone some minor changes and there is now a configurable, scalable and easy to use version available in two open source repositories. We present an overview of the latest stable HIVE-COTE, version 1.0, and describe how it differs to the original. We provide a walkthrough guide of how to use the classifier, and conduct extensive experimental evaluation of its predictive performance and resource usage. We compare the performance of HIVE-COTE to three recently proposed algorithms.

Item Type: Book Section
Uncontrolled Keywords: classification,hive-cote,heterogeneous ensembles,time series,theoretical computer science,computer science(all) ,/dk/atira/pure/subjectarea/asjc/2600/2614
Faculty \ School: Faculty of Science > School of Computing Sciences
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 05 Jan 2021 00:34
Last Modified: 04 Apr 2021 02:37
URI: https://ueaeprints.uea.ac.uk/id/eprint/78015
DOI: 10.1007/978-3-030-65742-0_1

Actions (login required)

View Item View Item