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Bayesian Combination of Multiple Plasma Glucose Predictors

In English

Författare

Redaktör

  • Michael Khoo

Summary, in English

This paper presents a novel on-line approach of merging multiple different predictors of plasma glucose into a single optimized prediction. Various different predictors are merged by recursive weighting into a single prediction using regularized optimization. The approach is evaluated on 12 data sets of type I diabetes data, using three parallel predictors. The performance of the combined prediction is better, or in par, with the best predictor for each evaluated data set. The results suggest that the outlined method could be a suitable way to improve prediction performance when using multiple predictors, or as a means to reduce the risk associated with definite a priori model selection.

Publiceringsår

2012

Språk

Engelska

Sidor

2839-2844

Publikation/Tidskrift/Serie

Proceedings of the 34th Annual Conference of the IEEE EMBS

Dokumenttyp

Konferensbidrag

Förlag

IEEE - Institute of Electrical and Electronics Engineers Inc.

Ämne

  • Control Engineering

Conference name

34th Annual Conference of the IEEE EMBS

Conference date

2012-08-28

Conference place

San Diego, CA, United States

Status

Published

Projekt

  • DIAdvisor

Forskningsgrupp

  • LCCC