International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 125 - Number 4 |
Year of Publication: 2015 |
Authors: Jinali Samir Gandhi, Khushali Deulkar |
10.5120/ijca2015905876 |
Jinali Samir Gandhi, Khushali Deulkar . A Compendium on the Contrasting Features of Data Mining Algorithms for the Diagnosis of Diabetes. International Journal of Computer Applications. 125, 4 ( September 2015), 7-9. DOI=10.5120/ijca2015905876
Data mining technology offers a user-oriented technique to hidden and novel patterns in the data. Because of rising diseases in the world, we are unable to evaluate all types of diseases and how to consume correct medicine for various diseases. Techniques of data mining are quite useful in finding the medicinal decision for the suitable diseases. Diabetes monitoring system is beneficial to diabetes patients. The diabetes system is useful not just for diabetes patients but also for those suspecting they are diabetic. The primary goal of this paper is to conduct a comparative analysis of decision tree algorithms namely ID3 and CART method focusing on diagnosis of diabetes.