Prediction on Domestic Violence in Bangladesh during the COVID-19 Outbreak Using Machine Learning Methods
نویسندگان
چکیده
The COVID-19 outbreak resulted in preventative measures and restrictions for Bangladesh during the summer of 2020—these unstable stressful times led to multiple social problems (e.g., domestic violence divorce). Globally, researchers, policymakers, governments, civil societies have been concerned about increase against women children ongoing pandemic. In Bangladesh, has increased this article, we investigated family among 511 families outbreak. Participants were given questionnaires answer, a period over ten days; predicted using machine learning-based model. To predict from our data set, applied random forest, logistic regression, Naive Bayes learning algorithms We employed an oversampling strategy named Synthetic Minority Oversampling Technique (SMOTE) chi-squared statistical test to, respectively, solve imbalance problem discover feature importance set. performances evaluated based on accuracy, precision, recall, F-score criteria. Finally, receiver operating characteristic (ROC) confusion matrices developed analyzed three algorithms. On average, model, with algorithms, 77%, 69%, 62% accuracy findings study indicate that is highly related two features: income level pandemic education members.
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ژورنال
عنوان ژورنال: Applied system innovation
سال: 2021
ISSN: ['2571-5577']
DOI: https://doi.org/10.3390/asi4040077