Volume : VIII, Issue : VI, June - 2019

A RANDOM FOREST ALGORITHM FOR CRIME PREDICTION OF BIGDATA ANALYSIS IN R

Selva Priya. T, M. Thuraipandian

Abstract :

Random forest is an Ensemble Classifier made using many Decision Tree models. Finding the place of criminal activity is vast amount to prevent it. The law enforcement agencies can work effectively and respond faster if they have good knowledge about crime pattern in different geological points of a city. Crime prediction using Random Forest Algorithm of Machine Learning with Supervised Learning Approach (Regression and Classification), Decision Tree Classifier and Big Data Analysis. We have collected the crime description dataset and experiment result shows that the ensemble Random Forest Algorithm outperformed the prediction crime with decision tree classifier and other classification algorithm in both performance and accuracy within the Bigdata. And the forecast results are visualized using R programming language. Bigdata is the collection of dataset.so large and complex difficult to handle hand, on database. It is useful for improving the accuracy and speed crime prediction.

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Article: Download PDF   DOI : 10.36106/ijsr  

Cite This Article:

A RANDOM FOREST ALGORITHM FOR CRIME PREDICTION OF BIGDATA ANALYSIS IN R, Selva Priya.T, M.Thuraipandian INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH : Volume-8 | Issue-6 | June-2019

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