Crime Mapping with Automatic Classifier System using Machine Learning and GIS

Abstract

Crime rate is increasing over the years, and it remains a great challenge for the government to track the crimes convicted. Each area has a pattern of which type of crime is happening and the crime knowledge is inevitable to control from the crime happening. Crime occurs in a sequence leaving hidden patterns. Thus the crime data is to be processed for finding underlying patterns, this project finds the patterns and insights about the crime data. Majorly being an unstructured data, this is been preprocessed and checked for future values. Crimes convicted are collected from a particular area (Indore in our case) and checked for predictions using Multi class Classification Algorithms like Random Forest and the future crime to be convicted in an area is predicted and visualizations are made accordingly. Many classification algorithms like support vector machines, decision trees, and random forest are used to classify and random forest shows better accuracy. Features to be given as input and output are selected by visualizing the data by graphs and plots.