caa a22 4500 606159606 CHVBK 20210128100625.0 cr unu---uuuuu 210128e20150401xx s 000 0 eng 10.1007/s00521-014-1742-6 doi (NATIONALLICENCE)springer-10.1007/s00521-014-1742-6 Nonstationary regression with support vector machines [Elektronische Daten] [Guillermo Grinblat, Lucas Uzal, Pablo Verdes, Pablo Granitto] In this work, we introduce a method for data analysis in nonstationary environments: time-adaptive support vector regression (TA-SVR). The proposed approach extends a previous development that was limited to classification problems. Focusing our study on time series applications, we show that TA-SVR can improve the accuracy of several aspects of nonstationary data analysis, namely the tasks of modelling and prediction, input relevance estimation, and reconstruction of a hidden forcing profile. The Natural Computing Applications Forum, 2014 Regression nationallicence Support vector machine nationallicence Nonstationary problems nationallicence Grinblat Guillermo CIFASIS, French Argentine International Center for Information and Systems Sciences, UAM (France)/UNR-CONICET (Argentina), Bv. 27 de Febrero 210 Bis, S2000EZP, Rosario, Argentina aut Uzal Lucas CIFASIS, French Argentine International Center for Information and Systems Sciences, UAM (France)/UNR-CONICET (Argentina), Bv. 27 de Febrero 210 Bis, S2000EZP, Rosario, Argentina aut Verdes Pablo CIFASIS, French Argentine International Center for Information and Systems Sciences, UAM (France)/UNR-CONICET (Argentina), Bv. 27 de Febrero 210 Bis, S2000EZP, Rosario, Argentina aut Granitto Pablo CIFASIS, French Argentine International Center for Information and Systems Sciences, UAM (France)/UNR-CONICET (Argentina), Bv. 27 de Febrero 210 Bis, S2000EZP, Rosario, Argentina aut Neural Computing and Applications Springer London 26/3(2015-04-01), 641-649 0941-0643 26:3<641 2015 26 521 https://doi.org/10.1007/s00521-014-1742-6 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-014-1742-6 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Grinblat Guillermo CIFASIS, French Argentine International Center for Information and Systems Sciences, UAM (France)/UNR-CONICET (Argentina), Bv. 27 de Febrero 210 Bis, S2000EZP, Rosario, Argentina aut NATIONALLICENCE 700 1- Uzal Lucas CIFASIS, French Argentine International Center for Information and Systems Sciences, UAM (France)/UNR-CONICET (Argentina), Bv. 27 de Febrero 210 Bis, S2000EZP, Rosario, Argentina aut NATIONALLICENCE 700 1- Verdes Pablo CIFASIS, French Argentine International Center for Information and Systems Sciences, UAM (France)/UNR-CONICET (Argentina), Bv. 27 de Febrero 210 Bis, S2000EZP, Rosario, Argentina aut NATIONALLICENCE 700 1- Granitto Pablo CIFASIS, French Argentine International Center for Information and Systems Sciences, UAM (France)/UNR-CONICET (Argentina), Bv. 27 de Febrero 210 Bis, S2000EZP, Rosario, Argentina aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/3(2015-04-01), 641-649 0941-0643 26:3<641 2015 26 521