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Central University of Tamil Nadu 
C.Vijayalakshmi,Shraddha Ramdas Bandekar 
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Design and Analysis of Machine Learning Algorithms for the reduction of crime rates in India 
Procedia Computer Science-Elsevier-Science Direct 
National Crime Records Bureau; K Means Clustering; Bayseian Neural Network; Levenberg Algorithm; Classifier Regression, Support Vector Machine; K-Nearest Neighbor; Optimization 
A country’s economic growth is adversely affected with the ever-increasing crimes every day. It is one of the most severe issues in our society and reducing the crime rates have become an extremely important task. Hence, it is very important to identify different factors, occurrence relations of crimes and thus determining optimized way to reduce crimes rates. For this a database must be maintained which keeps record of different crimes with details related to place, time and nature so on for future reference. This research work focuses on how machine learning algorithms can be designed and analyzed to reduce crime rates in India. By the means of machine learning techniques, determining the pattern relations among huge set of data has become easier. This research mainly depends on providing a prediction on crime type that might occur based on the location where it has already taken place. Machine learning has been used to develop a model by the use of training data set that have gone through the process of data cleaning and transformation. Analysis of data set along with its characteristics can be implemented with the aid of data visualization. The various factors are being identified and captured. Risk factors are being identified and predictive measures are designed which help in keeping society safe. Various clustering algorithms, optimization algorithms and statistical analysis has been done in this work.  
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C.Vijaya Lakshmi on 2020-09-03 
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