International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 178 - Number 14 |
Year of Publication: 2019 |
Authors: Mrinalini Jangra, Shaveta Kalsi |
10.5120/ijca2019918907 |
Mrinalini Jangra, Shaveta Kalsi . Naïve Bayes Approach for the Crime Prediction in Data Mining. International Journal of Computer Applications. 178, 14 ( May 2019), 33-37. DOI=10.5120/ijca2019918907
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.