Data Mining Models Comparison for Diabetes Prediction

• Published in: International journal of advanced computer science & applications Vol. 9; no. 8
• Main Authors: Azrar, Amina, Ali, Yasir, Awais, Muhammad, Zaheer, Khurram
• Format: Journal Article
• Language: English
• Published: West Yorkshire Science and Information (SAI) Organization Limited 2018
• Subjects: Algorithms; Clustering; Data mining; Datasets; Decision trees; Diabetes; Diabetes mellitus; Medical science
• ISSN: 2158-107X; 2156-5570; 2156-5570
• DOI: 10.14569/IJACSA.2018.090841

From the past few years, data mining got a lot of attention for extracting information from large datasets to find patterns and to establish relationships to solve problems. Well known data mining algorithms include classification, association, Naïve Bayes, clustering and decision tree. In medical science field, these algorithms help to predict a disease at early stage for future diagnosis. Diabetes mellitus is the most growing disease that needs to be predicted at its early stage as it is lifelong disease and there is no cure for it. This research is intended to provide comparison for different data mining algorithms on PID dataset for early prediction of diabetes.