Machine Learning Approaches on the Bankruptcy Modeling : Altman z-score, Neural Net, and CatBoost Classifier models

Language: English

Published by Eliva Press, 2024

9999319335 / 9789999319331

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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nach der Bestellung gedruckt Neuware - Printed after ordering - 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.

Seller Inventory # 9789999319331

Title
Machine Learning Approaches on the Bankruptcy Modeling : Altman z-score, Neural Net, and CatBoost Classifier models
Author
Murat Yazici
Publisher
Eliva Press
Publication year
2024
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
9999319335
ISBN 13
9789999319331
Item weight
78 grams
Dimensions
229x152x3 mm

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

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