HIVE-COTE 2.0: a new meta ensemble for time series classification

Abstract

The Hierarchical Vote Collective of Transformation-based Ensembles (HIVE-COTE) is a heterogeneous meta ensemble for time series classification. HIVE-COTE forms its ensemble from classifiers of multiple domains, including phase-independent shapelets, bag-of-words based dictionaries and phase-dependent intervals. Since it was first proposed in 2016, the algorithm has remained state of the art for accuracy on the UCR time series classification archive. Over time it has been incrementally updated, culminating in its current state, HIVE-COTE 1.0. During this time a number of algorithms have been proposed which match the accuracy of HIVE-COTE. We propose comprehensive changes to the HIVE-COTE algorithm which significantly improve its accuracy and usability, presenting this upgrade as HIVE-COTE 2.0. We introduce two novel classifiers, the Temporal Dictionary Ensemble (TDE) and Diverse Representation Canonical Interval Forest (DrCIF), which replace existing ensemble members. Additionally, we introduce the Arsenal, an ensemble of ROCKET classifiers as a new HIVE-COTE 2.0 constituent. We demonstrate that HIVE-COTE 2.0 is significantly more accurate than the current state of the art on 112 univariate UCR archive datasets and 26 multivariate UEA archive datasets.

References in corpus (17)

• Deep learning for time series classification: a review
• InceptionTime: Finding AlexNet for Time Series Classification
• ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels
• Benchmarking Multivariate Time Series Classification Algorithms
• Automatic time-series phenotyping using massive feature extraction
• Fast and Accurate Time Series Classification with WEASEL
• TS-CHIEF: A Scalable and Accurate Forest Algorithm for Time Series Classification
• Proximity Forest: An effective and scalable distance-based classifier for time series
• Should we really use post-hoc tests based on mean-ranks?
• The Canonical Interval Forest (CIF) Classifier for Time Series Classification
• Multivariate Time Series Classification with WEASEL+MUSE
• The Heterogeneous Ensembles of Standard Classification Algorithms (HESCA): the Whole is Greater than the Sum of its Parts
• The UEA multivariate time series classification archive, 2018
• Scalable Dictionary Classifiers for Time Series Classification
• The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classification
• From BOP to BOSS and Beyond: Time Series Classification with Dictionary Based Classifiers
• Applications of shapelet transform to time series classification of earthquake, wind and wave data

Cited by in corpus (5)

• A Review and Evaluation of Elastic Distance Functions for Time Series Clustering
• The FreshPRINCE: A Simple Transformation Based Pipeline Time Series Classifier
• Random Dilated Shapelet Transform: A New Approach for Time Series Shapelets
• Explainable classification of astronomical uncertain time series
• Active Transfer Prototypical Network: An Efficient Labeling Algorithm for Time-Series Data