Model Selection Under Sampling Uncertainty Using Fuzzy Numbers | A hybrid method

Bei Wen

ISBN 10: 3843394644 / ISBN 13: 9783843394642

Published by LAP LAMBERT Academic Publishing, 2011

About this Item

Model Selection Under Sampling Uncertainty Using Fuzzy Numbers | A hybrid method | Bei Wen | Taschenbuch | 104 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783843394642 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Seller Inventory # 107085462

Bibliographic Details

• Title: Model Selection Under Sampling Uncertainty Using Fuzzy Numbers | A hybrid method
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2011
• Language: English
• ISBN 10: 3843394644
• ISBN 13: 9783843394642
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 7D millimeters 220 millimeters width by 150 millimeters height by 7 millimeters depth
• Weight: 173 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

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.

About the Author

Bei held BSc in Computer Science and Economics. Thereafter she obtained a MSc in Economics & Informatics from Erasmus University, for which she produced a thesis on model selection under sampling uncertainty using fuzzy numbers. Now she is a PhD candidate at TU Delft, working for RI and KWR. Her field of interest is computing techniques.