A sequential sampling strategy for adaptive classification of computationally expensive data

Many real-world problems in engineering can be represented and solved as a data-driven classification problem, where the goal is to build a classifier that maps a given set of input parameters onto a corresponding class or label. In some cases, the collection of data samples can be computationally e...

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Veröffentlicht in:	Structural and multidisciplinary optimization 2017-04, Vol.55 (4), p.1425-1438
Hauptverfasser:	Singh, Prashant, Herten, Joachim van der, Deschrijver, Dirk, Couckuyt, Ivo, Dhaene, Tom
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive sampling Algorithms Classification Computational Mathematics and Numerical Analysis Data points Engineering Engineering Design Iterative methods Monte Carlo simulation Research Paper Sequential sampling Theoretical and Applied Mechanics
Online-Zugang:	Volltext
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