activity
20052017
most citedModelling reporting delays for disease surveillance data

133 citations · 150 across the 6 of their papers we have counts for

collaborators

6 papers

stat.AP2017★ 133 cited

Modelling reporting delays for disease surveillance data

Leonardo Bastos, Theodoros Economou, Marcelo Gomes +6

One difficulty for real-time tracking of epidemics is related to reporting delay. The reporting delay may be due to laboratory confirmation, logistic problems, infrastructure diffi…

cs.AI2010★ 1 cited

A Bayesian Methodology for Estimating Uncertainty of Decisions in Safety-Critical Systems

Vitaly Schetinin, Jonathan Fieldsend, Derek Partridge +4

Uncertainty of decisions in safety-critical engineering applications can be estimated on the basis of the Bayesian Markov Chain Monte Carlo (MCMC) technique of averaging over decis…

cs.AI2005

Comparison of the Bayesian and Randomised Decision Tree Ensembles within an Uncertainty Envelope Technique

Vitaly Schetinin, Jonathan E. Fieldsend, Derek Partridge +4

Multiple Classifier Systems (MCSs) allow evaluation of the uncertainty of classification outcomes that is of crucial importance for safety critical applications. The uncertainty of…

cs.AI2005

Estimating Classification Uncertainty of Bayesian Decision Tree Technique on Financial Data

Vitaly Schetinin, Jonathan E. Fieldsend, Derek Partridge +4

Bayesian averaging over classification models allows the uncertainty of classification outcomes to be evaluated, which is of crucial importance for making reliable decisions in app…

cs.AI2005

Experimental Comparison of Classification Uncertainty for Randomised and Bayesian Decision Tree Ensembles

V. Schetinin, D. Partridge, W. J. Krzanowski +4

In this paper we experimentally compare the classification uncertainty of the randomised Decision Tree (DT) ensemble technique and the Bayesian DT technique with a restarting strat…

cs.AI2005★ 16 cited

The Bayesian Decision Tree Technique with a Sweeping Strategy

V. Schetinin, J. E. Fieldsend, D. Partridge +4

The uncertainty of classification outcomes is of crucial importance for many safety critical applications including, for example, medical diagnostics. In such applications the unce…