{"product_id":"model-selection-under-sampling-uncertainty-using-fuzzy-numbers-von-bei-wen","title":"Model Selection Under Sampling Uncertainty Using Fuzzy Numbers","description":"\u003cp\u003eModel 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.\u003c\/p\u003e\u003cdiv class=\"aw-variant-hidden-subtitle-div\" id=\"aw-variant-subtitle-9783843394642\"\u003e\u003ch3\u003eA hybrid method\u003c\/h3\u003e\u003c\/div\u003e","brand":"Autorenwelt Shop","offers":[{"title":"Softcover - 9783843394642","offer_id":39469957218397,"sku":"9783843394642","price":49.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0940\/0622\/files\/e603123a-b779-496f-b794-fe3e37688a3d.jpg?v=1758175544","url":"https:\/\/shop.autorenwelt.de\/en\/products\/model-selection-under-sampling-uncertainty-using-fuzzy-numbers-von-bei-wen","provider":"Autorenwelt Shop","version":"1.0","type":"link"}