Combination of Naïve Bayes Classifier and K-Nearest Neighbor (cNK) in the Classification Based Predictive Models | Zendy

Elma Zannatul Ferdousy | Zendy; Md. Mafijul Islam | Zendy; Md. Abdul Matin | Zendy

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Combination of Naïve Bayes Classifier and K-Nearest Neighbor (cNK) in the Classification Based Predictive Models

Author(s) -

Elma Zannatul Ferdousy,

Md. Mafijul Islam,

Md. Abdul Matin

Publication year - 2013

Publication title -

computer and information science

Language(s) - English

Resource type - Journals

eISSN - 1913-8997

pISSN - 1913-8989

DOI - 10.5539/cis.v6n3p48

Subject(s) - computer science , naive bayes classifier , classifier (uml) , k nearest neighbors algorithm , bayes classifier , artificial intelligence , profitability index , machine learning , bayes' theorem , pattern recognition (psychology) , data mining , support vector machine , bayesian probability , finance , economics

In this study, we present a new classifier that combines the distance-based algorithm K-Nearest Neighbor and statistical based Naïve Bayes Classifier. That is equipped with the power of both but avoid their weakness. The performance of the proposed algorithm in terms of accuracy is experimented on some standard datasets from the machine-learning repository of University of California and compared with some of the art algorithms. The experiments show that in most of the cases the proposed algorithm outperforms the other to some extent. Finally we apply the algorithm for predicting profitability positions of some financial institutions of Bangladesh using data provided by the central bank.

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