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Erschienen in:
2019 | OriginalPaper | Buchkapitel
ClaRe: Classification and Regression Tool for Multivariate Time Series
verfasst von : Ricardo Cachucho, Stylianos Paraschiakos, Kaihua Liu, Benjamin van der Burgh, Arno Knobbe
Erschienen in: Machine Learning and Knowledge Discovery in Databases
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Abstract
As sensing and monitoring technology becomes more and more common, multiple scientific domains have to deal with big multivariate time series data. Whether one is in the field of finance, life science and health, engineering, sports or child psychology, being able to analyze and model multivariate time series has become of high importance. As a result, there is an increased interest in multivariate time series data methodologies, to which the data mining and machine learning communities respond with a vast literature on new time series methods.
However, there is a major challenge that is commonly overlooked; most of the broad audience of end users lack the knowledge on how to implement and use such methods. To bridge the gap between users and multivariate time series methods, we introduce the ClaRe dashboard. This open source web-based tool, provides to a broad audience a new intuitive data mining methodology for regression and classification tasks over time series. Code related to this paper is available at: https://github.com/parastelios/Accordion-Dashboard.