Results 251 to 260 of about 7,744,752 (291)

A comparative study of feature selection and feature extraction methods for financial distress identification. [PDF]

PeerJ Comput Sci
Kuizinienė D, Savickas P, Kunickaitė R, Juozaitienė R, Damaševičius R, Maskeliūnas R, Krilavičius T.   +6 more
europepmc   +1 more source

From data to immunity: the role of machine learning in advancing malaria vaccine research: a scoping review. [PDF]

Trop Dis Travel Med Vaccines
Khanday S, Sayeed M, Jafri NF, Jafri IF, Jafri RF, Ashraf G, Safwat S, Nasr DS.   +7 more
europepmc   +1 more source

Predicting BRICS NIFTY50 returns using XAI and S.A.F.E AI lens. [PDF]

Front Artif Intell
Ghosh I, Datta Chaudhuri T, Babaei G, Giudici P, Raffinetti E.   +4 more
europepmc   +1 more source

Money and mental health: a scoping review of financial variables, data sources, and analytical methods. [PDF]

Front Public Health
Adedeji O, Balaskas A, Coyle D, Gaynor K, Matthews M.   +4 more
europepmc   +1 more source

A comparison of alternative bankruptcy prediction models

Journal of Contemporary Accounting and Economics, 2010
Early models of bankruptcy prediction employed financial ratios drawn from pre-bankruptcy financial statements and performed well both in-sample and out-of-sample. Since then there has been an ongoing effort in the literature to develop models with even greater predictive performance. A significant innovation in the literature was the introduction into
Wu, Sean, Gaunt, Clive, Gray, Stephen
exaly   +6 more sources

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Machine learning models and bankruptcy prediction

Expert Systems With Applications, 2017
Machine learning models show improved bankruptcy prediction accuracy over traditional models.Various models were tested using different accuracy metrics.Boosting, bagging, and random forest models provide better results. There has been intensive research from academics and practitioners regarding models for predicting bankruptcy and default events, for
Herbert Kimura, Flavio Barboza, Edward I Altman   +2 more
exaly   +3 more sources

The bankruptcy risk matrix as a tool for interpreting the outcome of bankruptcy prediction models

Finance Research Letters, 2023
Christian Lohmann
exaly   +2 more sources

Bankruptcy prediction using multivariate grey prediction models

Grey Systems: Theory and Application, 2020
PurposeIn the face of complex and challenging economic and business environments, developing and implementing approaches to predict bankruptcy has become important for firms. Bankruptcy prediction can be regarded as a grey system problem because while factors such as the liquidity, solvency and profitability of a firm influence whether it goes bankrupt,
Yi-Chung Hu, Peng Jiang 0023, Hang Jiang, Jung-Fa Tsai   +3 more
openaire   +2 more sources

A neural network model for bankruptcy prediction

1990 IJCNN International Joint Conference on Neural Networks, 1990
A neural network model is developed for prediction of bankruptcy, and it is tested using financial data from various companies. The same set of data is analyzed using a more traditional method of bankruptcy prediction, multivariate discriminant analysis.
M. D. Odom, Ramesh Sharda
openaire   +2 more sources