ClaRe Dashboard: a Web-based Tool for Classification and Regression of Multivariate Time Series Data

Ricardo Cachucho, Stylianos Paraschiakos, Kaihua Liu, Benjamin van der Burgh & Arno Knobbe

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First Online: 18 January 2019

ECML PKDD 2018 publication: https://doi.org/10.1007/978-3-030-10997-4_51

Tutorial Video : https://www.youtube.com/watch?v=Vomhr9mBSBU

ClaRe Dashboard aims to provide toolkits to explore datasets in a visualized way, especially for multivariate time-series with mixed sampling rates. The dashboard was build with R Shiny package and it provides an experimental pipeline for time series data analysis with straightforward steps such as:

• Data uploading,
• Pre-processing (merge, manage missing values, plot etc.),
• Modeling (regression, classification), and
• Evaluation (model summary, visualization, export-import model).

Summary	Regression	Plot

Its friendly and interactive environment can be easily used from both experts and non-experts.

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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.

Authors and Affiliations

Authors and Affiliations

Leiden Institute of Advanced Computer Science, Leiden, The Netherlands

• Ricardo Cachucho, Kaihua Liu, Benjamin van der Burgh & Arno Knobbe

Leiden University Medical Center, Leiden, The Netherlands

• Ricardo Cachucho & Stylianos Paraschiakos

Corresponding author

Correspondence to Ricardo Cachucho .