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On-line Learning under Concept Drift

Eilers, Pieter Jan (2020) On-line Learning under Concept Drift. Master's Internship Report, Computing Science.

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Abstract

Using a modeling framework for the purpose of investigating on-line learning processes in non-stationary environments, we conduct experiments for a number of different situations. We consider the learning of a regression scheme in layered neural networks using sigmoidal and ReLU activation. In all situations, the target, i.e. the regression scheme, changes continuously while the system is trained from a stream of input data. We run Monte Carlo simulations in Student-Teacher scenarios equal number of student and teacher units, K = M. We extend this to the overlearnable case, where K>M. We include weight decay as a from of explicit forgetting and study its effects with regards to drift.

Item Type: Thesis (Master's Internship Report)
Supervisor name: Biehl, M. and Straat, M.J.C.
Degree programme: Computing Science
Thesis type: Master's Internship Report
Language: English
Date Deposited: 31 Jul 2020 13:34
Last Modified: 31 Jul 2020 13:34
URI: https://fse.studenttheses.ub.rug.nl/id/eprint/22948

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