Prediction and Prevention Analysis Using Machine Learning Algorithms for Detecting the Crime Data

Abstract

Crime is a fragment of substantial and predominating concerns in our society and its preclusion is key task Day to day there are huge numbers of offense committed sequentially. This requisite retain track of all the offense and preserving a database for same which may be used for succeeding reference. The present problem faced are maintaining of appropriate dataset of crime and evaluating this data to help in predicting and solving crimes in future. The objective of this project is to dataset which includes several crimes and forecasting the crime types which may transpire in future determining upon various constraints. In this intend, we will be utilizing the technique of machine learning and data science. Prior implementing of the replica model data pre-processing will be done ensuring this feature preference and grading will be done so that precision obtained will be excessive. The K-Nearest Neighbour (KNN) categorization and various other algorithms will be examined for crime data prediction and prevention one with progressing accuracy will be used for implementing. Delusion of dataset will be accepted in terms of graphical depiction of many occurrence for case in point at which duration the culprit rates are huge or at which month the culprit activities are peak. The essence purpose of this intend is to provide a jest idea of how machine learning can be used by the law enforcement agencies to detect, predict and prevent solving crimes at a much quicker rate and thus decrease the crime data.