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Multi-model ensemble framework for analysis of psychopathic traits in heinous crime convicts

Author

Listed:
  • Aman Singh

    (MIT-ADT University
    Birla Institute of Technology Mesra)

  • Subrajeet Mohapatra

    (Birla Institute of Technology Mesra)

Abstract

The correlation between psychiatric disorder and criminality has been the subject of intense debate and scrutiny in recent years, in light of multiple violent incidents in India and other nations. To determine the severity of psychopathic traits or tendencies in heinous crime convicts, a revised method is proposed, and its results are correlated with those of the PCL-R administered by an experienced psychologist. With a focus on multidimensional behavioral and personality characteristics, these schemes have evaluated the degree of psychopathy in violent offenders. Utilizing a fuzzy mutual information-based feature selection method, it is established that 62 features are statistically significant out of 68. Accordingly, a set of five base classifiers are used to construct the first layer of the stacking ensemble, and a single meta-learner is used to develop the second layer of the proposed stacked ensemble model. The average accuracy for the proposed stacked ensemble model with SVM-NL as meta-learner $$87.74\%$$ 87.74 % is the highest among all the configured stacked models. However, precision and f1-score for the proposed model are $$86\%$$ 86 % and $$85\%$$ 85 % respectively.

Suggested Citation

  • Aman Singh & Subrajeet Mohapatra, 2025. "Multi-model ensemble framework for analysis of psychopathic traits in heinous crime convicts," Journal of Computational Social Science, Springer, vol. 8(3), pages 1-28, August.
    • Handle: RePEc:spr:jcsosc:v:8:y:2025:i:3:d:10.1007_s42001-025-00391-x
    DOI: 10.1007/s42001-025-00391-x
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