Print Email Facebook Twitter Different approaches to fitting and extrapolating the learning curve Title Different approaches to fitting and extrapolating the learning curve Author KIM, DONGHWI (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Viering, T.J. (mentor) Loog, M. (mentor) Smaragdakis, G. (graduation committee) Degree granting institution Delft University of Technology Programme Computer Science and Engineering Project CSE3000 Research Project Date 2022-06-23 Abstract Extrapolation of the learning curve provides an estimation of how much data is needed to achieve the desired performance. It can be beneficial when gathering data is complex, or computation resource is limited. One of the essential processes of learning curve extrapolation is curve fitting. This research first analyses the behaviour of existing curve fitting methods such as Newton, Levenberg-Marquardt and Evolutionary algorithms when fitting different function models on learning curves. Furthermore, it also illustrates a few techniques to improve the learning curve fitting and extrapolation procedure. To reference this document use: http://resolver.tudelft.nl/uuid:25107a29-606e-4f76-bfa0-d1884fa4da02 Part of collection Student theses Document type bachelor thesis Rights © 2022 DONGHWI KIM Files PDF Research_Paper_Donghwi_Ki ... 11.077.pdf 3.02 MB Close viewer /islandora/object/uuid:25107a29-606e-4f76-bfa0-d1884fa4da02/datastream/OBJ/view