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Model Selection Under Sampling Uncertainty Using Fuzzy Numbers - Wen, Bei
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Model Selection Under Sampling Uncertainty Using Fuzzy Numbers - Taschenbuch

ISBN: 3843394644

Gebundene Ausgabe, ID: 10361861

A hybrid method - Buch, gebundene Ausgabe, 104 S., Beilagen: Paperback, Erschienen: 2011 LAP Lambert Acad. Publ. Model selection is one of the fundamental tasks of scientific inquiry. The most widely used methods such as ROC analysis do not take sampling uncertainty into account. To improve the robustness of model selection, the author developed a model selection method capable to incorporate sampling uncertainty. She captured the sampling uncertainty by using the bootstrap technique, and quantified the sampling uncertainty by introducing fuzzy numbers. In the book, the author applied the model selection system to a variety of real-world databases with respect to binary classifications. Among the tested datasets, the method performs in line with the traditional ROC analysis, whereas it provides the fuzzy presentation of ROC curves based on which not only the predictive accuracy but also the degree of sampling uncertainty can be addressed. In addition, the author developed a computer tool implementing the system, which eases the tedious procedures in model selection.

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Model Selection Under Sampling Uncertainty Using Fuzzy Numbers - Bei Wen
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Model Selection Under Sampling Uncertainty Using Fuzzy Numbers - neues Buch

ISBN: 9783843394642

ID: 7a49b4ddce49a311a15cb2d51fa850b6

Model selection is one of the fundamental tasks of scientific inquiry. The most widely used methods such as ROC analysis do not take sampling uncertainty into account. To improve the robustness of model selection, the author developed a model selection method capable to incorporate sampling uncertainty. She captured the sampling uncertainty by using the bootstrap technique, and quantified the sampling uncertainty by introducing fuzzy numbers. In the book, the author applied the model selection system to a variety of real-world databases with respect to binary classifications. Among the tested datasets, the method performs in line with the traditional ROC analysis, whereas it provides the fuzzy presentation of ROC curves based on which not only the predictive accuracy but also the degree of sampling uncertainty can be addressed. In addition, the author developed a computer tool implementing the system, which eases the tedious procedures in model selection. Buch / Broschur

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Model Selection Under Sampling Uncertainty Using Fuzzy Numbers - Wen, Bei
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Model Selection Under Sampling Uncertainty Using Fuzzy Numbers - Taschenbuch

2011

ISBN: 3843394644

Gebundene Ausgabe, ID: 10361861

A hybrid method - Buch, gebundene Ausgabe, 104 S., Beilagen: Paperback, Erschienen: 2011 LAP Lambert Acad. Publ.

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Model Selection Under Sampling Uncertainty Using Fuzzy Numbers
Autor:

Wen, Bei

Titel:

Model Selection Under Sampling Uncertainty Using Fuzzy Numbers

ISBN-Nummer:

3843394644

Model selection is one of the fundamental tasks of scientific inquiry. The most widely used methods such as ROC analysis do not take sampling uncertainty into account. To improve the robustness of model selection, the author developed a model selection method capable to incorporate sampling uncertainty. She captured the sampling uncertainty by using the bootstrap technique, and quantified the sampling uncertainty by introducing fuzzy numbers. In the book, the author applied the model selection system to a variety of real-world databases with respect to binary classifications. Among the tested datasets, the method performs in line with the traditional ROC analysis, whereas it provides the fuzzy presentation of ROC curves based on which not only the predictive accuracy but also the degree of sampling uncertainty can be addressed. In addition, the author developed a computer tool implementing the system, which eases the tedious procedures in model selection.

Detailangaben zum Buch - Model Selection Under Sampling Uncertainty Using Fuzzy Numbers


EAN (ISBN-13): 9783843394642
ISBN (ISBN-10): 3843394644
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2011

Buch in der Datenbank seit 16.03.2008 18:59:07
Buch zuletzt gefunden am 24.10.2015 08:22:44
ISBN/EAN: 3843394644

ISBN - alternative Schreibweisen:
3-8433-9464-4, 978-3-8433-9464-2

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