
Analysis on Prediction of Swine Flu Using Machine Learning Algorithms
LAP Lambert Academic Publishing
Published on 23. June 2020
Book
Paperback/Softback
76 pages
978-620-2-67239-9 (ISBN)
Description
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.
More details
Language
English
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 220 mm
Width: 150 mm
Thickness: 6 mm
Weight
131 gr
ISBN-13
978-620-2-67239-9 (9786202672399)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
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.