Main Article Content
Crime is one of the most predominant and alarming aspects in our society and its prevention is a vital task. Crime analysis is a systematic way of detecting and investigating patterns and trends in crime. Thus, it becomes necessary to study various reasons, factors and relationship between different crimes that are occurring and ?nding the most appropriate methods to control and avoid more crimes. The main objective of this project is to classify clustered crimes based on occurrence frequency during different years. Data mining is used broadly in terms of analysis, investigation and discovery of patterns for occurrence of different crimes. In this work, various clustering approaches of data mining are used to analyze the crime data. The K-Nearest Neighbour (KNN) classi?cation is used for crime prediction. The proposed system can predict regions which have high probability for crime rate and can forecast crime prone areas. Instead of focusing on causes of crime occurrence like criminal background of offender, political enmity etcit will focuse mainly on crime factors of each day.
How to Cite
, M. V. P. M. T. M. M. P. G. P. A. G. “Crime Rate Prediction Using KNN”. International Journal on Recent and Innovation Trends in Computing and Communication, vol. 6, no. 1, Jan. 2018, pp. 124 -, doi:10.17762/ijritcc.v6i1.1392.