Classification of Medical Dataset using Hybrid Feature Selection & Enhanced Decision Table Classification Approach
Abstract: Data mining is a emerging area of research that has been used for classification, clustering and association. In this paper classification approaches have been discussed that has been used for prediction of a class label to a instance available in the dataset. In this paper main concern of classification has been based on medical data classification. This classification of dataset can be used for prediction of various diseases to different patients on the basis of initial test values. In this paper diabetes dataset has been classified for prediction of accuracy of classification approach that use decision tables based classification using support and confidence computed for single instance available in dataset. In this paper purposed approach provides much better classification.
Keywords: Fuzzy KNN, Naive Bayes, classification approaches, Decision Tree
How to Cite?: Parneet Kaur, Deepak Aggarwal, "Classification of Medical Dataset using Hybrid Feature Selection & Enhanced Decision Table Classification Approach", Volume 6 Issue 3, March 2017, International Journal of Science and Research (IJSR), Pages: 335-338, https://www.ijsr.net/getabstract.php?paperid=ART20162609, DOI: https://dx.doi.org/10.21275/ART20162609