Classification of Radar Returns from Ionosphere Using NB-Tree and CFS IJTSRD
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.
by 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
call for paper Computer Security, international journal Parallel Computing, science journal