Model Selection Under Sampling Uncertainty Using Fuzzy Numbers

Language: English

Published by LAP LAMBERT Academic Publishing Feb 2011, 2011

3843394644 / 9783843394642

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This item is printed on demand - Print on Demand Titel. Neuware -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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 104 pp. Englisch.

Seller Inventory # 9783843394642

Title
Model Selection Under Sampling Uncertainty Using Fuzzy Numbers
Author
Bei Wen
Publisher
LAP LAMBERT Academic Publishing Feb 2011
Publication year
2011
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3843394644
ISBN 13
9783843394642
Item weight
173 grams
Dimensions
220x150x7 mm

buchversandmimpf2000

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