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  1. University of Information Technology
  2. Faculty of Computer Science

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

http://hdl.handle.net/20.500.12678/0000006179
http://hdl.handle.net/20.500.12678/0000006179
cae7cf51-528f-4585-b34c-512bf921cdd7
86a58e45-9c79-46bc-b481-4967a81f02c8
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Classification Classification of Radar Returns from Ionoshpere Using NB-Tree and CFS.pdf (1.5 Mb)
Publication type
Journal article
Upload type
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
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