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Reseach Article

Factorizing Data Technique using Naive Bayes

by Rutuja Mane, A. N. Bandal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 149 - Number 6
Year of Publication: 2016
Authors: Rutuja Mane, A. N. Bandal
10.5120/ijca2016911410

Rutuja Mane, A. N. Bandal . Factorizing Data Technique using Naive Bayes. International Journal of Computer Applications. 149, 6 ( Sep 2016), 5-8. DOI=10.5120/ijca2016911410

@article{ 10.5120/ijca2016911410,
author = { Rutuja Mane, A. N. Bandal },
title = { Factorizing Data Technique using Naive Bayes },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2016 },
volume = { 149 },
number = { 6 },
month = { Sep },
year = { 2016 },
issn = { 0975-8887 },
pages = { 5-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume149/number6/25999-2016911410/ },
doi = { 10.5120/ijca2016911410 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:54:39.728496+05:30
%A Rutuja Mane
%A A. N. Bandal
%T Factorizing Data Technique using Naive Bayes
%J International Journal of Computer Applications
%@ 0975-8887
%V 149
%N 6
%P 5-8
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Lack of deficiency of information in different particular areas like science, engineering as well as bio informatics has several problems. To overcome these issues, proposed a system and that system fusioning different kind of information inside single or individual unit for the preference or for the research of different existing areas. There is information fusioning is achieved through the matrix factorization based on heterogeneous information datasets that works together upon the proposed system. In proposed system new concept DFMF for the generation of prediction is utilized through the matrix factorization method. Similar system also accomplishes fusion as well as information prediction of the gene and pharmacologic activities.

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Index Terms

Computer Science
Information Sciences

Keywords

Data fusion Data integration Factorization Bioinformatics Cheminformatics