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A Data-Driven Method for Selecting Optimal Models Based on Graphical Visualisation of Differences in Sequentially Fitted ROC Model Parameters Cover

A Data-Driven Method for Selecting Optimal Models Based on Graphical Visualisation of Differences in Sequentially Fitted ROC Model Parameters

Data Science Journal
Volume 12 (2010): Issue 0
By: K S Mwitondi,  R E Moustafa and  A S Hadi  
Open Access
|May 2013

Authors

K S Mwitondi

k.mwitondi@shu.ac.uk

Sheffield Hallam University, Faculty of Arts, Computing, Engineering and Sciences, Sheffield S1 1WB, UK

R E Moustafa

moustafa@dmining-technology.com

George Washington University, Statistics Department, 2140 Pennsylvania Ave., NW, Washington DC, 20052, USA

A S Hadi

ahadi@aucegypt.edu

The American University in Cairo, Egypt/Cornell University, 291 Ives Hall, Cornell University, Ithaca, NY 14853-3901, USA
DOI: https://doi.org/10.2481/dsj.WDS-045 | Journal eISSN: 1683-1470
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Language: English
Published on: May 2, 2013
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
Bayesian error,
Data mining,
Data visualisation,
Decision trees,
Domain partitioning,
Optimal bandwidth,
ROC curves,
Visual analytics,
Youden Index

© 2013 K S Mwitondi, R E Moustafa, A S Hadi, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.

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