破产预测中期望最大化归算的平衡套袋——在罗马尼亚公司中的应用

Claudiu Clement
{"title":"破产预测中期望最大化归算的平衡套袋——在罗马尼亚公司中的应用","authors":"Claudiu Clement","doi":"10.56043/reveco-2022-0003","DOIUrl":null,"url":null,"abstract":"Bankruptcy prediction models are widely used by lending institutions, policy makers or investors. Despite the large volume of international research, limited studies have addressed the particularities of Romanian companies. Balanced Bagging is an Ensemble Method that uses a voting mechanism for a classification task. Expectation Maximization Imputation helps replacing the missing data. In this study we report a promising accuracy performance of 90.03% for the model of Balanced Bagging with Expectation Maximization Imputation on a dataset of more than 20,000 Romanian companies.","PeriodicalId":85430,"journal":{"name":"Revista economica","volume":"371 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"BALANCED BAGGING WITH EXPECTATION MAXIMIZATION IMPUTATION IN BANKRUPTCY PREDICTION – APPLICATION ON ROMANIAN COMPANIES\",\"authors\":\"Claudiu Clement\",\"doi\":\"10.56043/reveco-2022-0003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Bankruptcy prediction models are widely used by lending institutions, policy makers or investors. Despite the large volume of international research, limited studies have addressed the particularities of Romanian companies. Balanced Bagging is an Ensemble Method that uses a voting mechanism for a classification task. Expectation Maximization Imputation helps replacing the missing data. In this study we report a promising accuracy performance of 90.03% for the model of Balanced Bagging with Expectation Maximization Imputation on a dataset of more than 20,000 Romanian companies.\",\"PeriodicalId\":85430,\"journal\":{\"name\":\"Revista economica\",\"volume\":\"371 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Revista economica\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.56043/reveco-2022-0003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista economica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.56043/reveco-2022-0003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

破产预测模型被贷款机构、政策制定者或投资者广泛使用。尽管有大量的国际研究,但针对罗马尼亚公司特殊性的研究有限。平衡Bagging是一种集成方法,它对分类任务使用投票机制。期望最大化插值有助于替换缺失的数据。在这项研究中,我们报告了在超过20,000家罗马尼亚公司的数据集上,具有期望最大化Imputation的平衡装袋模型的有希望的准确性表现为90.03%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
BALANCED BAGGING WITH EXPECTATION MAXIMIZATION IMPUTATION IN BANKRUPTCY PREDICTION – APPLICATION ON ROMANIAN COMPANIES
Bankruptcy prediction models are widely used by lending institutions, policy makers or investors. Despite the large volume of international research, limited studies have addressed the particularities of Romanian companies. Balanced Bagging is an Ensemble Method that uses a voting mechanism for a classification task. Expectation Maximization Imputation helps replacing the missing data. In this study we report a promising accuracy performance of 90.03% for the model of Balanced Bagging with Expectation Maximization Imputation on a dataset of more than 20,000 Romanian companies.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信