Machine Learning Approaches on the Bankruptcy Modeling. This item is unavailable.
Language: English
Published by Eliva Press, 2024
- Softcover
- New

Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
5-star seller
AbeBooks seller since April 7, 2005
Unavailable
Softcover
Condition: New
£ 45.73
Item description from seller
New Book. Shipped from UK. Established seller since 2000.
Seller Inventory # L2-9789999319331
- Title
- Machine Learning Approaches on the Bankruptcy Modeling
- Author
- Yazici, Murat
- Publisher
- Eliva Press
- Publication year
- 2024
- Condition
- New
- Binding
- PAP
- Language
- English
- ISBN 10
- 9999319335
- ISBN 13
- 9789999319331
- Item weight
- 68 grams
This study includes Machine Learning (ML) approaches on the bankruptcy modeling. The Altman z-score model was selected as the subject of the study due to its widespread usage and extensive scientific validation, as well as its reputation as one of the most reliable tools for predicting bankruptcy. Typically, z-score models are evaluated in concert with other models or metrics. The Altman z-score remains a popular tool amongst investors, accountants, and stakeholders due to its versatility in application. The z-score model is especially useful due to its ease of use, compared to other predictive models. The models chosen for this study provided clear results for predicting a company’s financial stability in two regions as bankrupt and non-bankrupt, making it easy to compare between companies.
"Synopsis" may belong to another edition of this title.
Search results for Machine Learning Approaches on the Bankruptcy Modeling
There are 3 more copies of this bookView all results