Abstract
Recent years, more and more victims in crime in Los Angeles, especially after COVID-19. And women have more fear of crime and feel that they are more vulnerable than men. This article studies the future victim gender prediction by using algorithms in machine learning, like KNN, logistic regression and neural network. Machine learning has become more and more popular in the past few years. The results show that females are not seem as more vulnerable in crime than males in LA region. In addition, neural network method performs better than KNN and logistic regression, showing higher accuracy and f1-score. The accuracy of KNN is 59.82% and the f1-score is 65.36%. The accuracy of LR is 61.31% and f1-score is 67.76%. The accuracy of neural network is 62.58%, the f1-score is 70.22%. The result in this article can help the government to mitigate the heavy anxiety of females about being a victim in crimes.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
