Proceedings of the 2022 2nd International Conference on Business Administration and Data Science (BADS 2022)

<Previous Article In Volume
Next Article In Volume>

Research on the Criminal Recidivism Prediction Based on Machine Learning Algorithm

Authors
Jiaxin Zhang1, *
1Chinese University of HongKong (Shenzhen), Shenzhen, China
*Corresponding author. Email: 120090580@link.cuhk.edu.cn
Corresponding Author
Jiaxin Zhang
Available Online 29 December 2022.
DOI
10.2991/978-94-6463-102-9_134How to use a DOI?
Keywords
Machine Learning Algorithm; Recidivism Prediction
Abstract

Criminologists and social security personnel around the world have found that the risk of released criminals is much higher than that of people who have not committed crimes, and preventing people with criminal records from re-committing crimes should be one of the strategic priorities of social crime prevention. Therefore, risk assessment of criminal recidivism has been used to improve social security by predicting the criminal recidivism of offenders. In order to predict criminal recidivism, this article applied machine learning (ML) algorithms models (KNN, random forest, support vector machine and logistic regression) on the data set of the basic information about 10,000 criminal defendants in Broward County, Florida and their recidivism within two years. The predictive accuracy of models used in this article was between 0.64 and 0.67, with AUC ranging between 0.65–0.72. The AUC value of logistic regression is highest with 0.713 while support vector machine has the highest accuracy reaching to 0.671. This study provides a reference on selecting best method to predicting criminal recidivism.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 2022 2nd International Conference on Business Administration and Data Science (BADS 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
29 December 2022
ISBN
10.2991/978-94-6463-102-9_134
ISSN
2589-4900
DOI
10.2991/978-94-6463-102-9_134How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Jiaxin Zhang
PY  - 2022
DA  - 2022/12/29
TI  - Research on the Criminal Recidivism Prediction Based on Machine Learning Algorithm
BT  - Proceedings of the 2022 2nd International Conference on Business Administration and Data Science (BADS 2022)
PB  - Atlantis Press
SP  - 1297
EP  - 1306
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-102-9_134
DO  - 10.2991/978-94-6463-102-9_134
ID  - Zhang2022
ER  -