Diagnosis of Diabetes by using Data Mining Techniques

There are many classifiers that are used for diagnosis of diabetes but the result of this paper shows that how logistic regression having best accuracy among the other classifiers. Logistic regression removes the disadvantages of linear regression. There are different classifiers that are used for p...

Full description

Saved in:
Bibliographic Details
Published in:International journal of innovative technology and exploring engineering 2019-11, Vol.9 (1), p.2368-2372
Main Authors: kumar, Sachin, Kumar, Mr. Narender
Format: Article
Language:English
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:There are many classifiers that are used for diagnosis of diabetes but the result of this paper shows that how logistic regression having best accuracy among the other classifiers. Logistic regression removes the disadvantages of linear regression. There are different classifiers that are used for prediction. In the worldwide millions of peoples are suffering from diabetes according to WHO report. In the medical region, many researches have done with the help of data mining. The aim of this paper is to diagnosis of diabetes by using the best classifiers and providing best parameter tuning. The study helps to find whether a patient is enduring from diabetes or not using classification methods and it further investigate and evaluates the functioning of different classification in relations of precision, accuracy, recall & roc.
ISSN:2278-3075
2278-3075
DOI:10.35940/ijitee.L3174.119119