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

Aman Singh () and Subrajeet Mohapatra
Additional contact information
Aman Singh: MIT-ADT University
Subrajeet Mohapatra: Birla Institute of Technology Mesra

Journal of Computational Social Science, 2025, vol. 8, issue 3, No 12, 28 pages

Abstract: 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.

Keywords: Violent recidivism; Psychopathy risk markers; Quantitative risk assessment; Machine learning; Stacked ensemble (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s42001-025-00391-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jcsosc:v:8:y:2025:i:3:d:10.1007_s42001-025-00391-x

Ordering information: This journal article can be ordered from
http://www.springer. ... iences/journal/42001

DOI: 10.1007/s42001-025-00391-x

Access Statistics for this article

Journal of Computational Social Science is currently edited by Takashi Kamihigashi

More articles in Journal of Computational Social Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().