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Classification of Radar Returns from Ionosphere Using NB-Tree and CFS
http://hdl.handle.net/20.500.12678/0000006179
http://hdl.handle.net/20.500.12678/0000006179cae7cf51-528f-4585-b34c-512bf921cdd7
86a58e45-9c79-46bc-b481-4967a81f02c8
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Journal article | ||||||
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Publication | ||||||
Title | ||||||
Title | Classification of Radar Returns from Ionosphere Using NB-Tree and CFS | |||||
Language | en | |||||
Publication date | 2018-08-01 | |||||
Authors | ||||||
Aung Nway Oo | ||||||
Description | ||||||
This paper present an experimental 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 classification. The comparison of NB classifier and NB-Tree is done based on Ionosphere dataset from UCI machine learning repository. NBwith CFS gives better accuracy for classification of radar returns from ionosphere. | ||||||
Keywords | ||||||
classification, feature selection, NB, NB-Tree, CFS | ||||||
Journal articles | ||||||
5 | ||||||
International Journal of Trend in Scientific Research and Development (IJTSRD) | ||||||
1640-1642 | ||||||
2 |