On the optimal binary classifier with an application

被引：1

作者：

Lopez-Diaz, Maria Concepcion ^{[1
]}

Lopez-Diaz, Miguel ^{[2
]}

Martinez-Fernandez, Sergio ^{[3
]}

机构：

[1] Univ Oviedo, Dept Matemat, C-Federico Garcia Lorca 18, E-33007 Oviedo, Spain

[2] Univ Oviedo, Dept Estadist IO & D M, C-Federico Garcia Lorca 18, E-33007 Oviedo, Spain

[3] Un Auditoria Capital & Impairments, Banco Sabadell, C-Sena 12,PI Can St Joan, Sant Cugat Del Valles 08174, Barcelona, Spain

来源：

COMPUTATIONAL STATISTICS & DATA ANALYSIS | 2023年 / 181卷

关键词：

Binary classifier; Conditional probability; Extended modelling vector; Optimal classifier; ROC and CAP curves and indexes; DIAGNOSTIC-TESTS; CUSTOMER CHURN; AREA; PERFORMANCE; CURVE; MODEL;

D O I：

10.1016/j.csda.2022.107683

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The alternative accumulated improvement curve stochastic order is a criterion for the comparison of the performance of classifiers that predict binary responses. An explicit optimal classifier for this criterion is obtained. That optimal classifier has the largest ROC and CAP curves and indexes, that is, it is also optimal for the criteria based on the comparison of such curves and indexes. An application of the results to the search of the best classifier to predict clients of a bank which will make a transaction in the future is developed.(c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

引用

页数：14

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