Artificial immune network with feature selection for bank term deposit recommendation

Lu Xiao-Yong; Chu Xiao-Qiang; Chen Meng-Hui; Chang Pei-Chann; Chen Shih-Hsin

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Artificial immune network with feature selection for bank term deposit recommendation

机译：具有功能选择的人工免疫网络，用于推荐银行定期存款

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摘要

Artificial immune systems (AIS) have been widely utilized for pattern recognition and data analysis in various fields of science and technology, and artificial immune networks (AIN) are based on AIS. In this study, an artificial immune network is used for collaborative filtering as a classification model for bank term deposit recommendations, once feature selection has been applied to filter out key features for classification purposes. AIN is used to represent a network of customers with bank term deposits, and it can be adopted as a group decision-making model in predicting whether a new customer will have a term deposit or not. Formulae for calculating the affinity between an antigen and an antibody, and the affinity of an antigen to an immune network are also developed. A series of experiments are conducted, and the results are very encouraging. Despite the class imbalance problem in the test dataset, the proposed model outperformed other models, achieving the highest accuracy in testing.

机译：人工免疫系统（AIS）已在各个科学和技术领域中广泛用于模式识别和数据分析，而人工免疫网络（AIN）则基于AIS。在这项研究中，一旦特征选择已被应用以过滤出用于分类目的的关键特征，则将人工免疫网络用于协作过滤，作为银行定期存款建议的分类模型。 AIN用于表示具有银行定期存款的客户网络，并且可以用作预测新客户是否具有定期存款的团队决策模型。还开发了用于计算抗原和抗体之间的亲和力以及抗原对免疫网络的亲和力的公式。进行了一系列实验，结果令人鼓舞。尽管测试数据集中存在类不平衡问题，但所提出的模型优于其他模型，在测试中实现了最高的准确性。

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来源
《Journal of Intelligent Information Systems》 |2016年第2期|267-285|共19页
作者
Lu Xiao-Yong; Chu Xiao-Qiang; Chen Meng-Hui; Chang Pei-Chann; Chen Shih-Hsin;
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作者单位

Nanchang Univ, Sch Software, Nanchang, Peoples R China;

Yuan Ze Univ, Dept Informat Management, Chungli, Taiwan|Nanchang Univ, Sch Econ & Management, Nanchang, Peoples R China;

Yuan Ze Univ, Dept Informat Management, Chungli, Taiwan;

Yuan Ze Univ, Dept Informat Management, Chungli, Taiwan;

Cheng Shiu Univ, Dept Informat Management, Kaohsiung, Taiwan;

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原文格式 PDF
正文语种 eng
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关键词
Financial product; Term deposit; Artificial immune system; Collaborative filtering; Recommendation system;

机译：金融产品定期存款人为免疫系统协同过滤推荐系统;

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1. Artificial Immune System With Local Feature Selection for Short-Term Load Forecasting [J] . Grzegorz Dudek IEEE transactions on evolutionary computation . 2017,第1期

机译：具有局部特征选择的人工免疫系统用于短期负荷预测
2. Application of artificial immune network method for feature selection in predictive ADME model generation [J] . Das Shyam Sundar, Koneti Geervani, Bahl Jyotsna, Drug Metabolism Reviews . 2016,第1a4期

机译：人工免疫网络方法在预测Adme模型中的特征选择中的应用
3. Application of artificial immune network method for feature selection in predictive ADME model generation [J] . Das Shyam Sundar, Koneti Geervani, Bahl Jyotsna, Drug Metabolism Reviews . 2016,第1a4期

机译：人工免疫网络方法在预测Adme模型中的特征选择中的应用
4. Developement of Prediction in Clients’ Consent to a Bank Term Deposit Using Feature Selection [C] . Kinan Morani, Esra Kaya Ayana, Şeref Naci Engin 2018 6th International Conference on Control Engineering amp; Information Technology . 2018

机译：使用功能选择开发客户同意银行定期存款的预测
5. Feature selection of microarray data using genetic algorithms and artificial neural networks. [D] . Yacci, Paul. 2009

机译：使用遗传算法和人工神经网络对微阵列数据进行特征选择。
6. Artificial Neural Networks in Motion Analysis—Applications of Unsupervised and Heuristic Feature Selection Techniques [O] . Marion Mundt, Arnd Koeppe, Franz Bamer, 2020

机译：无监督和启发式特征选择技术的运动分析中的人工神经网络
7. This study aims at examining the effects of electronic banking on banks profitability in Jordan. How banking sector finds itself before a new fact imposed by technology revolution and digits to change their work mechanisms from traditional means to electronic means and the challenges banks face as a result. Furthermore, this study investigates the reasons behinds providing electronic banking services through internet, their impact on banking services in general and banks profitability in particular. Risks and challenges involved are discussed Results and recommendations are included. Results revealed that electronic banking service has a negative effect on banks profitability on the short term. The importance of this study and the factors that make it unique is that, it discusses solely the topic of the effects of electronic banking on banks profitability, while most of other studies discuss the topic in general term. The findings of the study are the impact of electronic banking on banks profitability will be feature of the short run due to the capital investment by the banks on infrastructure and training but will be positive on the long run. [O] . Ahmad Z. Siam 2006

机译：这项研究旨在研究电子银行业务对约旦银行盈利能力的影响。在技术革命和数字技术将新的工作机制从传统手段转变为电子手段以及银行面临的挑战之前，银行业如何发现自己。此外，本研究调查了通过互联网提供电子银行服务背后的原因，它们对总体银行服务的影响，尤其是对银行盈利能力的影响。讨论了涉及的风险和挑战包括结果和建议。结果显示，电子银行服务在短期内对银行的盈利能力有负面影响。这项研究及其独特性的重要性在于，它仅讨论电子银行业务对银行盈利能力的影响这一主题，而其他大多数研究则从总体上讨论该主题。该研究的结果是，由于银行对基础设施和培训的资本投资，电子银行对银行盈利能力的影响将是短期的特征，但从长远来看将是积极的。
8. Selection of Psychophysiological Features Across Subjects for Classifying Workload Using Artificial Neural Networks [R] . Laine, T. I. 1999

机译：用人工神经网络选择跨学科分类工作量的心理生理特征

Artificial immune network with feature selection for bank term deposit recommendation

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