Classification of Radar Returns from Ionosphere Using NB-Tree and CFS

This paper present an experimental study of the different classifiers namely Naïve Bayes (NB) and NB-Tree for classification of radar returns from Ionosphere dataset. Correlation-based Feature Subset Selection (CFS) is also used for attribute selection. The purpose is to achieve the efficient result for classification. The comparison of NB classifier and NB-Tree is done based on Ionosphere dataset from UCI machine learning repository. NB-Tree classifier with CFS gives better accuracy for classification of radar returns from ionosphere. Aung Nway Oo"Classification of Radar Returns from Ionosphere Using NB-Tree and CFS" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-5 , August 2018, URL: http://www.ijtsrd.com/papers/ijtsrd17126.pdf http://www.ijtsrd.com/computer-science/data-miining/17126/classification-of-radar-returns-from-ionosphere-using-nb-tree-and-cfs/aung-nway-oo