Crime prediction using classification rule mining
Islam, Md Nimul
Farid, Abu Talha
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Data mining produce workable significant information from a huge amount of discrete data. Data mining is the process of naturally looking huge stores of information to find patterns and prediction that go past basic examination. Data mining also assumes an imperative part as far as prediction and analysis. We are using here three different classification algorithm in Weka. The algorithm we have used here Naive Bayes, Bayes Net, One-R. We have collected data from Dhaka metropolitan police, Chittagong metropolitan police, Bangladesh police, Newspaper and due to sensitive data from a secret agent. The main objective of this paper is to predict place from crime occurred in the last few years. The law enforcement agencies ought to in this way have the capacity to anticipate such increments or abatements or patterns in crime for example,the number of murder,robbery,burglaries or any such crime that may happen in a specific zone in a specific month, year, or any timespan or the general number of crime happening in a nation in a specific year later on, or any other expectation or projection of future crime measurements. So that the law enforcement agency can find out the place easily where the crime rate is high to take proper action, thus reducing the crime rate.