ANALYSIS ON PREDICTION OF SWINE FLU USING MACHINE LEARNING ALGORITHMS

The Data mining technique can be used in collaboration With a K-NN classifiers, Naïve Bayes, Random Forest, Support Vector Machine algorithms which used in diagnosing Swine flu disease virus affected across different persons based on their Symptoms. This proposed approach showed some Promising results which may lead to further attempts to utilize information technology for diagnosing virus from which patients are suffering from Swine flu. Here we used K-NN Classification, Naïve Bayes, Random Forest, SVM rules which are easy to interpret. In future, we will try to get more the accuracy results for the swine flu disease which helps to find different parameters using different data mining techniques as per suggested by doctors.

About the author

Ms.Y.Deepika had completed her Under Graduation recently at Vignan's Institute of Information Technology, Visakhapatnam. Dr.N.Thirupathi Rao is currently associated with Vignan's Institute of Information Technology, Visakhapatnam. Dr.Debnath Bhattacharyya is currently associated with Koneru Lakshmaiah Deemed to be University, KLEF, Guntur, AP. 

Product details

• Authors: Debnat Bhattacharyya, Debnath Bhattacharyya, Thirupathi Ra N, Thirupathi Rao N., Deepik Y, Deepika Y.
• Publisher: LAP Lambert Academic Publishing
• Languages: English
• Product format: Paperback / Softback
• Released: 01.01.2020
• No. of pages: 76
• Dimensions: 150 mm x 220 mm x 5 mm
• Weight: 131 g
• Subjects: Guides; Natural sciences, medicine, IT, technology > IT, data processing