Predicting the Vulnerability of Women to Intimate Partner Violence in South Africa: Evidence from Tree-based Machine Learning Techniques

Amusa, Lateef B.; Bengesai, Annah V.; Khan, Hafiz T. A.

doi:10.1177/0886260520960110

Predicting the Vulnerability of Women to Intimate Partner Violence in South Africa: Evidence from Tree-based Machine Learning Techniques

Intimate partner violence (IPV) is a pervasive social challenge with severe health and demographic consequences. Global statistics indicate that more than a third of women have experienced IPV at some point in their lives. In South Africa, IPV is considered a significant contributor to the country?s...

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VerfasserInnen:	Amusa, Lateef B. (Verfasst von) ; Bengesai, Annah V. (Verfasst von) ; Khan, Hafiz T. A. (Verfasst von)
Medienart:	Elektronisch Aufsatz
Sprache:	Englisch
Veröffentlicht:	2022
In:	Journal of interpersonal violence Jahr: 2022, Band: 37, Heft: 7/8, Seiten: NP5228-NP5245
Online-Zugang:	Volltext (lizenzpflichtig)
Verfügbarkeit prüfen:	HBZ Gateway
Schlagwörter:	South Africa Decision Tree Intimate Partner Violence Machine Learning