Naïve Bayes Approach for the Crime Prediction in Data Mining (original) (raw)

2019, International journal of computer applications

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Crime Prediction using Naïve Bayes Algorithm

2021

This paper presents the detection of the crimes happening in India. The criminal offences lead to certain punishment according to Indian Penal Code (IPC). For particular crime particular sections are assigned to punish the criminal or convicts with jail terms and fine. On this pre-processed data sets, by applying Naïve Bayesian algorithm we create a predictive model which analyze the data and helps to predict the crime type in a near future. We are using a dataset to apply Naïve Bayes algorithm to predict the crimes in India. Keywords— Naïve Bayes algorithm, Dataset

Mining the crime data using naïve Bayes model

Indonesian Journal of Electrical Engineering and Computer Science

A massive number of documents on crime has been handled by police departments worldwide and today's criminals are becoming technologically elegant. One obstacle faced by law enforcement is the complexity of processing voluminous crime data. Approximately 439 crimes have been registered in sanchez mira municipality in the past seven years. Police officers have no clear view as to the pattern crimes in the municipality, peak hours, months of the commission and the location where the crimes are concentrated. The naïve Bayes modelis a classification algorithm using the Rapid miner auto model which is used and analyze the crime data set. This approach helps to recognize crime trends and of which, most of the crimes committed were a violation of special penal laws. The month of May has the highest for index and non-index crimes and Tuesday as for the day of crimes. Hotspots were barangay centro 1 for non-index crimes and barangay centro 2 for index crimes. Most non-index crimes commit...

Performance Analysis of Naïve Bayes Algorithm on Crime Data Using Rapid Miner

International Journal of Advanced Research in Computer Science, 2017

Crime, when someone does any unlawful activity, the intensity level of crime can be from very low to very high. In current society, crime exist everywhere in distinct form, and if we collect all the data related to different crime, that data would be very large in volume which can be managed through data mining techniques. Using various data mining techniques, lot of conclusion can be drawn like rise or fall in particular type of crime, percentage of particular crime, time when crime mostly or less happens, area in which maximum or minimum crime happens etc. In this paper, we use rapid miner data mining tool and naive Bayes classification algorithm to show the different types of crime. By using crime data on classification algorithm with rapid miner tool we tries to demonstrate that how efficiently naive Bayes algorithm can manage this data and the accuracy of result. As there is a probability of crime prediction and naive Bayes algorithm gives result based on probability, thus the ...

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