Araştırma Makalesi

Violence Detection with Machine Learning: A Sociodemographic Approach

Sayı: 44 31 Aralık 2022
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Violence Detection with Machine Learning: A Sociodemographic Approach

Abstract

This study suggests that by implementing machine learning methods on a sociodemographic data set can be helpful in preventing domestic violence. This approach is important in predicting high-risk factors that an offender may cause and it offers treatment, and financial or mental health aids in order to prevent domestic violence. In this sense, this proposal is critical at a personal and social level in creating a secure and healthy environment as well as empowering an equal society. In our study, we use k-nearest neighbor (k-nn), support vector machine (SVM), decision tree (DT), and Gaussian Naive Bayes (GNB) machine learning algorithms for the prediction analysis. We provide the comparison of the classifiers with precision, recall, F1 score, and accuracy performance measures. According to our analysis, the decision tree (DT) performs the best performance in terms of accuracy.

Keywords

Kaynakça

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Ayrıntılar

Birincil Dil

İngilizce

Konular

Mühendislik

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

31 Aralık 2022

Gönderilme Tarihi

28 Aralık 2022

Kabul Tarihi

31 Aralık 2022

Yayımlandığı Sayı

Yıl 2022 Sayı: 44

Kaynak Göster

APA
Ensari, T., Ensari, B., & Dağtekin, M. (2022). Violence Detection with Machine Learning: A Sociodemographic Approach. Avrupa Bilim ve Teknoloji Dergisi, 44, 104-107. https://doi.org/10.31590/ejosat.1225896

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