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@article{146245,
        author = {richa patel and kinjal thakar and rina raval},
        title = {A review on various classification algorithms to predict the crime status},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {4},
        number = {12},
        pages = {50-54},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=146245},
        abstract = {in recent past, crime rate is becoming high in most highly populated country. Security is an aspect which is given higher priority by all governments in the world hence the significant task of to predict the crimes over data history. Now a days increasing user of the internet in the world is going rapidly hence cybercrime rate is also increasing. In data mining lots of algorithms are available to solve the mining problems. The crime profiling and zoning can be modelled with utilization of data mining. The predicted crime status can help to police department for investigation of criminal. Classification and clustering may prove the better methods for predict the crime status in data mining. Naïve Bayesian, k-Nearest Neighbour[3], Neural Networks may prove much better classifiers in comparisons of decision tree and support vector machine in data mining},
        keywords = {Data mining in crime data, Classification, clustering, predict crime status, K means algorithm , K-NN , decision tree, J48, SVM},
        month = {},
        }