Data mining and Region Prediction Based on Crime Using Random Forest

dc.contributor.author	Raza, Dewan Mamun
dc.contributor.author	Victor, Debasish Bhattacharjee
dc.date.accessioned	2022-04-16T09:18:24Z
dc.date.available	2022-04-16T09:18:24Z
dc.date.issued	2021-04-12
dc.identifier.uri	http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/7842
dc.description.abstract	Crime is one of the most critical problems of the today's world which affects the normal life of the society and it breaks the social, and economical flow of a country. The scenario is the same for Bangladesh. This paper focused on prediction of the areas based on crimes instead of the opposite. This will also be beneficial to predict crimes occurred in different cities in certain timeframe. And knowing the future trend the law enforcement and detectives will be able to take precautionary steps which will in turn reduce the rate of such events. Here, Random Forest algorithm is used to predict the regions (AKA district) based on different crime rates	en_US
dc.language.iso	en_US	en_US
dc.publisher	International Conference on Artificial Intelligence and Smart Systems (ICAIS), IEEE	en_US
dc.subject	Crime	en_US
dc.subject	Region	en_US
dc.subject	District	en_US
dc.subject	City	en_US
dc.subject	Prediction	en_US
dc.subject	Bangladesh police	en_US
dc.subject	Machine learning	en_US
dc.subject	Data mining	en_US
dc.title	Data mining and Region Prediction Based on Crime Using Random Forest	en_US
dc.type	Article	en_US