A feature selection prediction technique for healthcare using naive bayes algorithm

ISSN: 22773878
0Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.

Abstract

Nowadays, the data volume and its types and formats of data are very vast and complex in the field of health care. Bigdata is referred to as a huge volume of data that are complex to be handled with traditional database. The bigdata in healthcare plays an important role in enhancing treatments and facilities, hence the healthcare departments are in need to understand as much as they can, about the patient to prevent them from serious illness in the future. A feature selection technique is used for selecting subsets from large datasets and naive Bayes algorithm is used for classifying the datasets. The aim of the proposed work is to provide right information and accurate data to the organization, so that the data provided after predicting will enable the organization to ensure treating the patient’s illness which may occur in the future by the help of the results found by Feature selection classification technique. Then the classification is done through naïve bayes algorithm (NB) that analyse data and gives the prediction accuracy of the future outcome healthcare datasets.

Cite

CITATION STYLE

APA

Betty Jane, J., & Ganesh, E. N. (2019). A feature selection prediction technique for healthcare using naive bayes algorithm. International Journal of Recent Technology and Engineering, 8(1), 1467–1472.

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free