ClaRe: Classification and Regression Tool for Multivariate Time Series

• Published in: Machine Learning and Knowledge Discovery in Databases Vol. 11053; pp. 682 - 686
• Main Authors: Cachucho, Ricardo, Paraschiakos, Stylianos, Liu, Kaihua, van der Burgh, Benjamin, Knobbe, Arno
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2019; Springer International Publishing
• Series: Lecture Notes in Computer Science
• ISBN: 9783030109967; 3030109968
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-030-10997-4_51

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.