A Naive Bayes Algorithm of Data Mining Method for Clustering of Data

  • Syed Shareefunnisa, Simhadri Chinna Gopi, Anusha Viswanadapalli, Praveen Kumar Nelapati

Abstract

A significant research theory that will have a wide range of application in future is Data mining. The invisible information in a Data is found by using this Data mining. This paper deals with a Naive Bayes Algorithm of Data mining Method for Clustering of Data. The major part of the cluster is a feature extraction/feature selection. This implies recognition of set of options in a set, since the selection of features is considered a necessary method. In this paper, data mining algorithm of naive bayes is used to predict product recommendations. This naive bayes algorithm is implemented on a set of products with the help of WEKA data mining software tool. The handling of missing data is carried out by applying an approach of A Unique Category (AUC) for obtaining better performance than the exported classifier model. The result shows that application of this AUC handling of missing data increase the accuracy of classifier model.

Published
2020-06-01
How to Cite
Syed Shareefunnisa, Simhadri Chinna Gopi, Anusha Viswanadapalli, Praveen Kumar Nelapati. (2020). A Naive Bayes Algorithm of Data Mining Method for Clustering of Data. International Journal of Advanced Science and Technology, 29(06), 8021 -. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/24354