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RETRACTED ARTICLE: Intelligent hybrid model for financial crisis prediction using machine learning techniques

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This article was retracted on 14 November 2022

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Abstract

Financial crisis prediction (FCP) plays a vital role in the economic phenomenon. The precise prediction of the number and possibility of failing firms acts as an index of the growth and strength of a nation’s economy. Traditionally, several methods have been presented for effective FCP. On the other hand, the classification performance and prediction accuracy and data legality is not good enough for practical applications. In addition, many of the developed methods perform well for some of the particular dataset but not adaptable to different dataset. Hence, there is a requirement to develop an efficient prediction model for better classification performance and adaptable to diverse dataset. This paper presents a cluster based classification model, comprises of two stages: improved K-means clustering and a fitness-scaling chaotic genetic ant colony algorithm (FSCGACA) based classification model. In the first stage, an improved K-means algorithm is devised to eliminate the wrongly clustered data. Then, a rule-based model is selected to design to fit the given dataset. At the end, FSCGACA is employed for seeking the optimal parameters of the rule-based model. The proposed algorithm is employed to a collection of three benchmark dataset which include qualitative bankruptcy dataset, Weislaw dataset and Polish dataset. A detailed statistical analysis of the dataset is also given. The results analysis ensured that the presented FCP model is superior to other classification model based on the different measures and also found to be more appropriate for diverse dataset.

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Authors and Affiliations

  1. Department of Computer Science, Pondicherry University, Puducherry, India

    J. Uthayakumar

  2. Faculty of Commerce, Mansoura University, Mansoura, Egypt

    Noura Metawa

  3. Anderson College of Business, Regis University, Denver, USA

    Noura Metawa

  4. School of Computing, Kalasalingam Academy of Research and Education, Krishnankoil, India

    K. Shankar

  5. Department of Electronics and Instrumentation Engineering, B. S. Abdur Rahman Crescent Institute of Science and Technology, Chennai, India

    S. K. Lakshmanaprabu

Authors
  1. J. Uthayakumar
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  2. Noura Metawa
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  3. K. Shankar
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  4. S. K. Lakshmanaprabu
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Corresponding author

Correspondence to Noura Metawa.

Additional information

This article has been retracted. Please see the retraction notice for more detail: https://doi.org/10.1007/s10257-022-00586-z"

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Uthayakumar, J., Metawa, N., Shankar, K. et al. RETRACTED ARTICLE: Intelligent hybrid model for financial crisis prediction using machine learning techniques. Inf Syst E-Bus Manage 18, 617–645 (2020). https://doi.org/10.1007/s10257-018-0388-9

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  • DOI: https://doi.org/10.1007/s10257-018-0388-9

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