Analysis and Prediction of Diabetes Diseases

Abstract

Today, the data mining is popular as an important
field in healthcare sector for deeper study of medical data
and providing accurate predictions of diseases.Various
diseases such as stroke, diabetes, cancer, hypothyroid and
heart disease, etc are identified using data mining
techniques. To predict if the individual is infected by
diabetes or not, the required dataset was downloaded. As
the number of people affected by diabetes increases day by
day this prediction helps to find if the patient is diabetic or
not.
In machine learning analyzing and summarizing data from
different aspects into valuable information is the main
point of view. The data from different dimensions are
analysed then it categorize the relationships. WEKA is a
data analysis tool for machine learning classification. The
vital technique with more applications in various fields is
called Machine learning. It is used to classify each item in a
set of data into one predefined set of classes. This research
paper presents the analysis and prediction of diabetes
diseases. The proposed work focuses on machine learning
techniques and using the WEKA tool.