Naïve Bayes Approach for the Crime Prediction in Data Mining
Author(s) -
Mrinalini Jangra,
Shaveta Kalsi
Publication year - 2019
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2019918907
Subject(s) - computer science , bayes' theorem , naive bayes classifier , data mining , data science , artificial intelligence , bayesian probability , support vector machine
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.
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