Improving the Accuracy of Cancer Prediction by Ensemble Confidence Evaluation
Created by W.Langdon from
gp-bibliography.bib Revision:1.8187
- @InProceedings{Affenzeller:2013:EUROCAST,
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author = "Michael Affenzeller and Stephan M. Winkler and
Herbert Stekel and Stefan Forstenlechner and Stefan Wagner",
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title = "Improving the Accuracy of Cancer Prediction by
Ensemble Confidence Evaluation",
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booktitle = "Computer Aided Systems Theory - EUROCAST 2013",
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year = "2013",
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editor = "Roberto Moreno-Diaz and Franz Pichler and
Alexis Quesada-Arencibia",
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volume = "8111",
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series = "Lecture Notes in Computer Science",
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pages = "316--323",
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address = "Las Palmas de Gran Canaria, Spain",
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month = feb # " 10-15",
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publisher = "Springer",
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note = "Revised Selected Papers, Part I",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-642-53855-1",
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language = "English",
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URL = "
http://dx.doi.org/10.1007/978-3-642-53856-8_40",
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DOI = "
doi:10.1007/978-3-642-53856-8_40",
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size = "8 pages",
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abstract = "This paper discusses a novel approach for the
prediction of breast cancer, melanoma and cancer in the
respiratory system using ensemble modelling techniques.
For each type of cancer, a set of unequally complex
predictors are learnt by symbolic classification based
on genetic programming. In addition to standard
ensemble modeling, where the prediction is based on a
majority voting of the prediction models, two
confidence parameters are used which aim to quantify
the trustworthiness of each single prediction based on
the clearness of the majority voting. Based on the
calculated confidence of each ensemble prediction,
predictions might be considered uncertain. The
experimental part of this paper discusses the increase
of accuracy that can be obtained for those samples
which are considered trustable depending on the ratio
of predictions that are considered trustable.",
- }
Genetic Programming entries for
Michael Affenzeller
Stephan M Winkler
Herbert Stekel
Stefan Forstenlechner
Stefan Wagner
Citations