Learning Optimal Time Series Combination and Pre-Processing by Smart Joins
dc.contributor.author | Gil Lertxundi, Amaia | |
dc.contributor.author | Quartulli, Marco Francesco | |
dc.contributor.author | García Olaizola, Igor | |
dc.contributor.author | Sierra Araujo, Basilio | |
dc.date.accessioned | 2020-10-14T11:43:13Z | |
dc.date.available | 2020-10-14T11:43:13Z | |
dc.date.issued | 2020-09-11 | |
dc.identifier.citation | Applied Sciences 10(18) : (2020) // Article ID 6346 | es_ES |
dc.identifier.issn | 2076-3417, | |
dc.identifier.uri | http://hdl.handle.net/10810/46887 | |
dc.description.abstract | In industrial applications of data science and machine learning, most of the steps of a typical pipeline focus on optimizing measures of model fitness to the available data. Data preprocessing, instead, is often ad-hoc, and not based on the optimization of quantitative measures. This paper proposes the use of optimization in the preprocessing step, specifically studying a time series joining methodology, and introduces an error function to measure the adequateness of the joining. Experiments show how the method allows monitoring preprocessing errors for different time slices, indicating when a retraining of the preprocessing may be needed. Thus, this contribution helps quantifying the implications of data preprocessing on the result of data analysis and machine learning methods. The methodology is applied to two case studies: synthetic simulation data with controlled distortions, and a real scenario of an industrial process. | es_ES |
dc.description.sponsorship | This research has been partially funded by the 3KIA project (ELKARTEK, Basque Government). | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | |
dc.subject | optimization | es_ES |
dc.subject | machine learning | es_ES |
dc.subject | preprocessing | es_ES |
dc.title | Learning Optimal Time Series Combination and Pre-Processing by Smart Joins | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.date.updated | 2020-09-25T13:30:36Z | |
dc.rights.holder | 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). | es_ES |
dc.relation.publisherversion | https://www.mdpi.com/2076-3417/10/18/6346 | es_ES |
dc.identifier.doi | 10.3390/app10186346 | |
dc.departamentoes | Ciencia de la computación e inteligencia artificial | |
dc.departamentoeu | Konputazio zientziak eta adimen artifiziala |
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Except where otherwise noted, this item's license is described as 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).