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Paper Title

MULTIVALUE PREDICTION IN TWITTER USING NAIVE BAYES ALGORITHM

Authors

ANITHA M V , SANTHI M , Dr. ELIZABETH ISSAAC

Keywords

Multi value prediction, Text mining, Naïve Bayes

Abstract

Techniques for learning choice standards are as effectively connected to numerous issue areas, specifically when comprehension and translation of the educated model are vital many problem domains, in particular when understanding and interpretation of the learned model is necessary. In numerous genuine issues, might want to anticipate differently related (ostensible or numeric) target properties at the same time. While a few techniques for learning decides that foresee numerous objectives on the double exist. In the most widely recognized machine picking up setting, one predicts the estimation of a single target quality, straight out or numeric. Characteristic speculation of this setting is to anticipate multiple target qualities all the while. The undertaking comes in two marginally extraordinary flavors. . In multi-target expectation, all objective characteristics are (similarly) critical and anticipated at the same time with a solitary model. Perform multiple tasks learning then again, initially centered around a solitary target quality and utilized the rest for help as it were. These days, be that as it may, perform multiple tasks models ordinarily anticipate each objective property separately however within any event somewhat particular models. In this undertaking, we pick the Twitter application for multivalve expectation. Twitter is one of online networking with in excess of 500 million clients and 400 million tweets for every day. In any composed twits of twitter clients, it contains a different feeling. The vast majority of the examination on the utilization of web-based life conclusion investigation classifications into three positive, negative and neutral. In this task, to identify the feeling of Twitter clients that are characterized into 6 classes, specifically joy, miserable, furious, shock, appall and dread.

How To Cite

Choose the style your journal or department asks for, then copy it. Every version below is generated from this paper's own record.

IJRTI — journal style
"MULTIVALUE PREDICTION IN TWITTER USING NAIVE BAYES ALGORITHM", IJRTI - International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.4, Issue 4, page no.73 - 76, April-2019, Available :https://ijrti.org/papers/IJRTI1904016.pdf
APA — 7th edition
V, A. M., M, S., & ISSAAC, E. (2019). MULTIVALUE PREDICTION IN TWITTER USING NAIVE BAYES ALGORITHM. International Journal for Research Trends and Innovation, 4(4), 73 - 76. https://ijrti.org/viewpaperforall.php?paper=IJRTI1904016
MLA — 9th edition
V, ANITHA M, et al. "MULTIVALUE PREDICTION IN TWITTER USING NAIVE BAYES ALGORITHM." International Journal for Research Trends and Innovation, vol. 4, no. 4, 2019, pp. 73 - 76, https://ijrti.org/viewpaperforall.php?paper=IJRTI1904016.
Chicago — 17th, bibliography
V, ANITHA M, SANTHI M, and ELIZABETH ISSAAC. "MULTIVALUE PREDICTION IN TWITTER USING NAIVE BAYES ALGORITHM." International Journal for Research Trends and Innovation 4, no. 4 (2019): 73 - 76. https://ijrti.org/viewpaperforall.php?paper=IJRTI1904016.
Harvard — author–date
V, A.M., M, S. and ISSAAC, E. (2019) 'MULTIVALUE PREDICTION IN TWITTER USING NAIVE BAYES ALGORITHM', International Journal for Research Trends and Innovation, 4(4), pp. 73 - 76. Available at: https://ijrti.org/viewpaperforall.php?paper=IJRTI1904016
IEEE — numbered reference
A. M. V, S. M and E. ISSAAC, "MULTIVALUE PREDICTION IN TWITTER USING NAIVE BAYES ALGORITHM," IJRTI, vol. 4, no. 4, pp. 73 - 76, Apr. 2019.
Vancouver — biomedical
V AM, M S, ISSAAC E. MULTIVALUE PREDICTION IN TWITTER USING NAIVE BAYES ALGORITHM. IJRTI. 2019 Apr;4(4):73 - 76.
AMA — 11th edition
V AM, M S, ISSAAC E. MULTIVALUE PREDICTION IN TWITTER USING NAIVE BAYES ALGORITHM. IJRTI. 2019;4(4):73 - 76. Accessed at https://ijrti.org/viewpaperforall.php?paper=IJRTI1904016
BibTeX — Zotero, Mendeley, LaTeX
@article{IJRTI1904016, author = {ANITHA M V and SANTHI M and ELIZABETH ISSAAC}, title = {MULTIVALUE PREDICTION IN TWITTER USING NAIVE BAYES ALGORITHM}, journal = {International Journal for Research Trends and Innovation}, volume = {4}, number = {4}, pages = {73 - 76}, year = {2019}, month = {April}, issn = {2456-3315}, url = {https://ijrti.org/viewpaperforall.php?paper=IJRTI1904016} }
RIS — EndNote, RefWorks
TY - JOUR AU - V, ANITHA M AU - M, SANTHI AU - ISSAAC, ELIZABETH TI - MULTIVALUE PREDICTION IN TWITTER USING NAIVE BAYES ALGORITHM T2 - International Journal for Research Trends and Innovation JA - IJRTI VL - 4 IS - 4 PY - 2019 SN - 2456-3315 UR - https://ijrti.org/viewpaperforall.php?paper=IJRTI1904016 SP - 73 EP - 76 ER -

Issue

Volume 4 Issue 4, April-2019
Pages : 73 - 76

Other Publication Details

Paper Reg. ID IJRTI_180761
Published Paper ID IJRTI1904016
Downloads 205,650
Research Area Engineering
Country Kottayam, Kerala, India
Published April 2019

About Publisher

International Journal for Research Trends and Innovation Published by IJRTI (JW Publication)
2456-3315 ISSN
10.57 Impact Factor
2016 ESTD Year
Open Access
Impact Factor 10.57 calculated by Google Scholar and Semantic Scholar.
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Licence

© 2019 — Authors hold the copyright of this article. This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.
 Disclaimer: The content, data and findings in this article are based on the authors’ research and have been peer-reviewed for academic purposes only. Readers are advised to verify all information before practical or commercial use. The journal and its editorial board are not liable for any errors, losses or consequences arising from its use.

Declarations

Funding

No external funding was received for this study.

Conflict of Interest

The authors declare that they have no conflict of interest.

Acknowledgements

The authors would like to thank the reviewers and the editorial board of International Journal for Research Trends and Innovation for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.

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