Naïve Bayes Approach for the Crime Prediction in Data Mining
Mrinalini Jangra,Shaveta Kalsi +1 more
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TLDR
To improve accuracy of crime prediction technique of Naïve Bayes is applied and it is evaluated that Na naïve Bayes give higher accuracy as compared to KNN for the crime prediction.Abstract:
Prediction analysis is the analysis in which future trends and outcomes are predicted on the basis of assumption. It is the analysis in which future trends and outcomes are predicted on the basis of assumption. Machine learning techniques and regression techniques are the two approaches that have been utilized in order to conduct predictive analytics. In the conducting predictive analytics, machine learning techniques are widely utilized and become popular as large scale datasets handled by it is effective manner and provide high performance. It provides the results with uniform characteristics and noisy data. The KNN is the popular technique which is applied in the prediction analysis. To improve accuracy of crime prediction technique of Naïve Bayes is applied in this research work. It is evaluated that Naïve Bayes give higher accuracy as compared to KNN for the crime prediction.read more
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References
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Proceedings ArticleDOI
Crime Pattern Detection Using Data Mining
TL;DR: This work looked at use of clustering algorithm for a data mining approach to help detect the crimes patterns and speed up the process of solving crime, and developed a weighting scheme for attributes here to deal with limitations of out of the box clustering tools and techniques.
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Crime prediction using Twitter sentiment and weather
TL;DR: By testing the model's ability to predict future crime on each area of the city, it is observed that the model surpassed the benchmark model, which predicts crime incidents using kernel density estimation.
Proceedings ArticleDOI
Crime analysis and prediction using data mining
TL;DR: This work has an approach between computer science and criminal justice to develop a data mining procedure that can help solve crimes faster and is focusing mainly on crime factors of each day.
Journal ArticleDOI
Using machine learning algorithms to analyze crime data
TL;DR: The scope of this project is to prove how effective and accurate the machine learning algorithms used in data mining analysis can be at predicting violent crime patterns.
Journal ArticleDOI
Crime Prediction Based On Crime Types And Using Spatial And Temporal Criminal Hotspots
TL;DR: An analysis study is introduced by combining the findings of Denver crimes dataset with its demographics information in order to capture the factors that might affect the safety of neighborhoods and to help agencies to predict future crimes in a specific location within a particular time.