Improving the Naive Bayes Classifier via a Quick Variable Selection Method Using Maximum of Entropy

Improving the Naive Bayes Classifier via a Quick Variable Selection Method Using Maximum of Entropy

Variable selection methods play an important role in the field of attribute mining. The Naive Bayes (NB) classifier is a very simple and popular classification method that yields good results in a short processing time. Hence, it is a very appropriate classifier for very large datasets. The method h...

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Bibliographic Details
Main Authors: Joaquín Abellán, Javier G. Castellano
Format: Article
Language:English
Published: MDPI AG 2017-05-01
Series:Entropy
Subjects:
variable selection
classification
Naive Bayes
imprecise probabilities
uncertainty measures
Online Access:http://www.mdpi.com/1099-4300/19/6/247

Internet

http://www.mdpi.com/1099-4300/19/6/247

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