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Ultra-fast meta-parameter optimization for time series similarity measures with application to nearest neighbour classification

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Main Authors: Chang Wei, Tan, Matthieu, Herrmann, Geoffrey I., Webb
Format: Book
Language:English
Published: Springer 2023
Subjects:
UCR
Online Access:https://link.springer.com/article/10.1007/s10115-022-01827-w
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8302
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spelling oai:localhost:PNK-83022023-04-25T08:54:09Z Ultra-fast meta-parameter optimization for time series similarity measures with application to nearest neighbour classification Chang Wei, Tan Matthieu, Herrmann Geoffrey I., Webb UCR CC BY Nearest neighbour similarity measures are widely used in many time series data analysis applications. They compute a measure of similarity between two time series. Most applications require tuning of these measures’ meta-parameters in order to achieve good performance. However, most measures have at least O(L2) complexity, making them computationally expensive and the process of learning their meta-parameters burdensome, requiring days even for datasets containing only a few thousand series. In this paper, we propose ULTRAFASTMPSEARCH, a family of algorithms to learn the meta-parameters for different types of time series distance measures. These algorithms are significantly faster than the prior state of the art. Our algorithms build upon the state of the art, exploiting the properties of a new efficient exact algorithm which supports early abandoning and pruning for most time series distance measures. We show on 128 datasets from the UCR archive that our new family of algorithms are up to an order of magnitude faster than the previous state of the art. 2023-04-25T08:54:09Z 2023-04-25T08:54:09Z 2023 Book https://link.springer.com/article/10.1007/s10115-022-01827-w https://dlib.phenikaa-uni.edu.vn/handle/PNK/8302 en application/pdf Springer
institution Digital Phenikaa
collection Digital Phenikaa
language English
topic UCR
spellingShingle UCR
Chang Wei, Tan
Matthieu, Herrmann
Geoffrey I., Webb
Ultra-fast meta-parameter optimization for time series similarity measures with application to nearest neighbour classification
description CC BY
format Book
author Chang Wei, Tan
Matthieu, Herrmann
Geoffrey I., Webb
author_facet Chang Wei, Tan
Matthieu, Herrmann
Geoffrey I., Webb
author_sort Chang Wei, Tan
title Ultra-fast meta-parameter optimization for time series similarity measures with application to nearest neighbour classification
title_short Ultra-fast meta-parameter optimization for time series similarity measures with application to nearest neighbour classification
title_full Ultra-fast meta-parameter optimization for time series similarity measures with application to nearest neighbour classification
title_fullStr Ultra-fast meta-parameter optimization for time series similarity measures with application to nearest neighbour classification
title_full_unstemmed Ultra-fast meta-parameter optimization for time series similarity measures with application to nearest neighbour classification
title_sort ultra-fast meta-parameter optimization for time series similarity measures with application to nearest neighbour classification
publisher Springer
publishDate 2023
url https://link.springer.com/article/10.1007/s10115-022-01827-w
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8302
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score 8.891787

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