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Explainable Machine Learning for Credit Risk Management When Features are Dependent 当特征相互依赖时,用于信用风险管理的可解释机器学习
IF 1 Q2 Mathematics Pub Date : 2024-03-01 DOI: 10.1080/15366367.2023.2261186
Thanh Thuy Do, Golnoosh Babaei, Paolo Pagnottoni
Complex Machine Learning (ML) models used to support decision-making in peer-to-peer (P2P) lending often lack clear, accurate, and interpretable explanations. While the game-theoretic concept of Sh...
用于支持点对点(P2P)借贷决策的复杂机器学习(ML)模型往往缺乏清晰、准确和可解释的说明。虽然博弈论的 Sh...
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引用次数: 0
Validation and Implementation of Customer Classification System using Machine Learning 利用机器学习验证和实施客户分类系统
IF 1 Q2 Mathematics Pub Date : 2024-02-29 DOI: 10.1080/15366367.2023.2246111
Hyemin Yoon, HyunJin Kim, Sangjin Kim
We have maintained the customer grade system that is being implemented to customers with excellent performance through customer segmentation for years. Currently, financial institutions that operat...
多年来,我们一直坚持通过客户细分,对业绩优秀的客户实施客户等级制度。目前,经营...
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引用次数: 0
Estimation of Finite Population Variance Under Stratified Sampling in the Presence of Measurement Errors 存在测量误差时分层抽样下的有限人口方差估计
IF 1 Q2 Mathematics Pub Date : 2024-02-29 DOI: 10.1080/15366367.2023.2247618
Abdul Haq, Muhammad Usman, Manzoor Khan
Measurement errors may significantly distort the properties of an estimator. In this paper, estimators of the finite population variance using the information on first and second raw moments of the...
测量误差可能会严重扭曲估计器的特性。本文利用有限人口方差的第一和第二原始矩的信息来估计有限人口方差。
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引用次数: 0
Uncertainty in Artificial Neural Network Models: Monte-Carlo Simulations Beyond the GUM Boundaries 人工神经网络模型的不确定性:超越 GUM 边界的蒙特卡洛模拟
IF 1 Q2 Mathematics Pub Date : 2024-02-29 DOI: 10.1080/15366367.2023.2246112
A.M. Sadek, Fahad Al-Muhlaki
In this study, the accuracy of the artificial neural network (ANN) was assessed considering the uncertainties associated with the randomness of the data and the lack of learning. The Monte-Carlo al...
在这项研究中,考虑到与数据的随机性和缺乏学习有关的不确定性,对人工神经网络(ANN)的准确性进行了评估。Monte-Carlo 分析法是一种用于计算和分析数据的...
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引用次数: 0
A Study on the Relationship Between Deep Learning and Statistical Models 深度学习与统计模型之间的关系研究
IF 1 Q2 Mathematics Pub Date : 2024-02-29 DOI: 10.1080/15366367.2023.2246707
Il Do Ha
Recently, deep learning has become a pervasive tool in prediction problems for structured and/or unstructured big data in various areas including science and engineering. In particular, deep neural...
近来,深度学习已成为科学和工程等各个领域中结构化和/或非结构化大数据预测问题的普遍工具。特别是,深度神经...
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引用次数: 0
Environmental Behavior in the Private Sphere – Development and Evaluation of the Personal Pro-Environmental Behavior (PPB) Scale 私人领域的环保行为--个人环保行为(PPB)量表的开发与评估
IF 1 Q2 Mathematics Pub Date : 2024-02-29 DOI: 10.1080/15366367.2023.2246113
Matthias Winfried Kleespies, Viktoria Feucht, Til Jonas Tille, Alina Miriam Bambach, Eva Gricar, Maximilian Claus, Michael Matthias Günther Konertz, Laura Kokott, Valentin Rupp, Valentin Bergmann, Volker Wenzel, Paul Wilhelm Dierkes
Human pro-environmental behavior in the private sphere is an important factor which influences nature and the environment and thus can contribute to the management of environmental problems. Althou...
人类在私人领域的环保行为是影响自然和环境的一个重要因素,因此有助于环境问题的管理。尽管...
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引用次数: 0
Modeling Complex Data from Simulations to Assess Middle School Students’ NGSS-Aligned Science Learning 模拟复杂数据模型,评估初中生与 NGSS 一致的科学学习情况
IF 1 Q2 Mathematics Pub Date : 2024-02-29 DOI: 10.1080/15366367.2023.2246754
Emily K. Toutkoushian, Kihyun Ryoo
The Next Generation Science Standards (NGSS) delineate three interrelated dimensions that describe what students should know and how they should engage in science learning. These present significan...
下一代科学标准》(NGSS)划分了三个相互关联的维度,描述了学生应该知道什么以及他们应该如何参与科学学习。这三个维度提出了重要的...
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引用次数: 0
How Randomly are Students Random Responding to Your Questionnaire? Within-Person Variability in Random Responding Across Scales in the TIMSS 2015 Eighth-Grade Student Questionnaire 学生随机回答问卷的随机性如何?TIMSS 2015 八年级学生问卷中各量表随机回答的人内差异性
IF 1 Q2 Mathematics Pub Date : 2024-02-20 DOI: 10.1080/15366367.2023.2203972
Saskia van Laar, Jianan Chen, Johan Braeken
Questionnaires in educational research assessing students’ attitudes and beliefs are low-stakes for the students. As a consequence, students might not always consistently respond to a questionnaire...
在教育研究中,评估学生态度和信念的问卷对学生的影响不大。因此,学生可能不会始终如一地回答问卷......
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引用次数: 0
Scale Reliability Evaluation Using Bayesian Analysis: A Latent Variable Modeling Procedure 使用贝叶斯分析法进行量表可靠性评估:潜变量建模程序
IF 1 Q2 Mathematics Pub Date : 2024-02-20 DOI: 10.1080/15366367.2023.2183799
Tenko Raykov, George Marcoulides, Randall Schumacker
An application of Bayesian factor analysis for evaluation of scale reliability is discussed, which is developed within the framework of latent variable modeling. The method permits direct point and...
本文讨论了在潜在变量建模框架内开发的贝叶斯因子分析在量表信度评估中的应用。该方法允许直接点和...
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引用次数: 0
Two-Stage Classification Method for Individual Workout Status Prediction with Machine Learning Approach 用机器学习方法预测个人锻炼状态的两阶段分类法
IF 1 Q2 Mathematics Pub Date : 2024-02-20 DOI: 10.1080/15366367.2023.2246109
Yoonjae Noh, YoonIl Yoon, Sangjin Kim
The default risk, one of the main risk factors for bonds, should be measured and reflected in the bond yield. Particularly, in the case of financial companies that treat bonds as a major product, f...
违约风险是债券的主要风险因素之一,应在债券收益率中加以衡量和反映。尤其是将债券作为主要产品的金融公司,其债券收益率更应反映违约风险。
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引用次数: 0
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Measurement-Interdisciplinary Research and Perspectives
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