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Crime Prediction Using Random Forest Model

Shalini G, Mounika V, Sannidhi U P, Swathi Y N, Dr. Deepak N R, Omprakash B

Abstract


The most serious issue in present scenario is crime, which disrupts the people’s lives. The crime will not occur not only in certain time of human lives but it will occur at any time in person’s life, whether they are travelling home from work or going on trip etc. In terms of public safety, crime prediction is required. We can predict the crimes using Random Forest Model. This model will help the authorized officers do their work efficiently as well as effectively so that they can avoid the crime before it occurs. Depending on the quality of the data, the crime prediction accuracy can vary differently. The amount of crimes that occur can be decreased with effective crime prediction. Models such as Polynomial and Linear Regressions limits in capturing intricacy of crime data , however Regression model demonstrates encouraging results. The main significance that we need to keep in mind is that selecting suitable machine learning methods for tasks related to prediction of crimes.


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References


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