Data mining and Region Prediction Based on Crime Using Random Forest

dc.contributor.authorRaza, Dewan Mamun
dc.contributor.authorVictor, Debasish Bhattacharjee
dc.date.accessioned2022-04-16T09:18:24Z
dc.date.available2022-04-16T09:18:24Z
dc.date.issued2021-04-12
dc.description.abstractCrime 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
dc.identifier.otherhttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/7842
dc.identifier.urihttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/7842
dc.language.isoen_US
dc.publisherInternational Conference on Artificial Intelligence and Smart Systems (ICAIS), IEEE
dc.sourceDIU Institutional Repository
dc.subjectCrime
dc.subjectRegion
dc.subjectDistrict
dc.subjectCity
dc.subjectPrediction
dc.subjectBangladesh police
dc.subjectMachine learning
dc.subjectData mining
dc.titleData mining and Region Prediction Based on Crime Using Random Forest
dc.typeArticle

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