A Financial Distress Prediction Model Based on Sparse Algorithm and Support Vector Machine
المؤلفون المشاركون
Zeng, Sen
Li, Yaqin
Yang, Wanjun
Li, Yanru
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-11-29
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
Classification learning is a very important issue in machine learning, which has been widely used in the field of financial distress warning.
Some researches show that the prediction model framework based on sparse algorithm has better performance than the traditional model.
In this paper, we explore the financial distress prediction based on grouping sparsity.
Feature selection of sparse algorithm plays an important role in classification learning, because many redundant and irrelevant features will degrade performance.
A good feature selection algorithm would reduce computational complexity and improve classification accuracy.
In this study, we propose an algorithm for feature selection classification prediction based on feature attributes and data source grouping.
The existing financial distress prediction model usually only uses the data from financial statement and ignores the timeliness of company sample in practice.
Therefore, we propose a corporate financial distress prediction model that is better in line with the practice and combines the grouping sparse principal component analysis of financial data, corporate governance characteristics, and market transaction data with support vector machine.
Experimental results show that this method can improve the prediction efficiency of financial distress with fewer characteristic variables.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zeng, Sen& Li, Yaqin& Yang, Wanjun& Li, Yanru. 2020. A Financial Distress Prediction Model Based on Sparse Algorithm and Support Vector Machine. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1196084
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zeng, Sen…[et al.]. A Financial Distress Prediction Model Based on Sparse Algorithm and Support Vector Machine. Mathematical Problems in Engineering No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1196084
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zeng, Sen& Li, Yaqin& Yang, Wanjun& Li, Yanru. A Financial Distress Prediction Model Based on Sparse Algorithm and Support Vector Machine. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1196084
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1196084
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر