Classification of Medical Dataset using Hybrid Feature Selection & Enhanced Decision Table Classification Approach
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 137 | Views: 357

Research Paper | Computer Science & Engineering | India | Volume 6 Issue 3, March 2017 | Popularity: 6.2 / 10


     

Classification of Medical Dataset using Hybrid Feature Selection & Enhanced Decision Table Classification Approach

Parneet Kaur, Deepak Aggarwal


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


Edition: Volume 6 Issue 3, March 2017


Pages: 335 - 338



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Parneet Kaur, Deepak Aggarwal, "Classification of Medical Dataset using Hybrid Feature Selection & Enhanced Decision Table Classification Approach", International Journal of Science and Research (IJSR), Volume 6 Issue 3, March 2017, pp. 335-338, https://www.ijsr.net/getabstract.php?paperid=ART20162609, DOI: https://www.doi.org/10.21275/ART20162609

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