A Financial Distress Prediction Model Based on Sparse Algorithm and Support Vector Machine
Joint Authors
Zeng, Sen
Li, Yaqin
Yang, Wanjun
Li, Yanru
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-11-29
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract 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.
American Psychological Association (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
Modern Language Association (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
American Medical Association (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
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1196084