Hate Crime Analysis based on Artificial Intelligence Methods

نویسندگان

چکیده

Hate crimes always take a toll on American citizens, which harms social security. It is essential for researchers to explore the factors, lead hate crimes. This research find out relationship between and factors including income inequality, median household income, race using Machine Learning methods. Learning, as an important branch in Artificial Intelligence, good way finding relationships things. The based dataset of rates 2016 U.S. presidential election well every state from 2010 2015. Simply linear regression multiple are used describe that influence crime rate their contributions, such share white poverty or non-white residents, income. Then, K-means applied classify into 5 levels according rate. Furthermore, KNearest Neighbors demonstrate prediction crime. At last, histogram indicate variance different states. From regression, four highest correlation coefficients with can be found out, noncitizen, turn. Income inequality has coefficient it only by implementing we obtain R square values, 0.44 2015 0.33 K-Nearest method, predicted accuracy 40% applying Adding factor, rises 50%. In summary, have high impact could predict about

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ژورنال

عنوان ژورنال: E3S web of conferences

سال: 2021

ISSN: ['2555-0403', '2267-1242']

DOI: https://doi.org/10.1051/e3sconf/202125101062