Open Access   Article Go Back

Classification of Pulsar Candidates Using an Ensemble Model

Sanat Kumar Sahu1

Section:Research Paper, Product Type: Journal Paper
Volume-9 , Issue-8 , Page no. 81-83, Aug-2021

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v9i8.8183

Online published on Aug 31, 2021

Copyright © Sanat Kumar Sahu . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

XML View
PDF Download

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: Sanat Kumar Sahu, “Classification of Pulsar Candidates Using an Ensemble Model,” International Journal of Computer Sciences and Engineering, Vol.9, Issue.8, pp.81-83, 2021.

MLA Style Citation: Sanat Kumar Sahu "Classification of Pulsar Candidates Using an Ensemble Model." International Journal of Computer Sciences and Engineering 9.8 (2021): 81-83.

APA Style Citation: Sanat Kumar Sahu, (2021). Classification of Pulsar Candidates Using an Ensemble Model. International Journal of Computer Sciences and Engineering, 9(8), 81-83.

BibTex Style Citation:
@article{Sahu_2021,
author = {Sanat Kumar Sahu},
title = {Classification of Pulsar Candidates Using an Ensemble Model},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {8 2021},
volume = {9},
Issue = {8},
month = {8},
year = {2021},
issn = {2347-2693},
pages = {81-83},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5385},
doi = {https://doi.org/10.26438/ijcse/v9i8.8183}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v9i8.8183}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5385
TI - Classification of Pulsar Candidates Using an Ensemble Model
T2 - International Journal of Computer Sciences and Engineering
AU - Sanat Kumar Sahu
PY - 2021
DA - 2021/08/31
PB - IJCSE, Indore, INDIA
SP - 81-83
IS - 8
VL - 9
SN - 2347-2693
ER -

VIEWS PDF XML
228 211 downloads 139 downloads
  
  
           

Abstract

In the past, researchers study candidate filters used to solve the problem for the last years. Pulsar is a type of star, which is interested in the great scientific topic. Through which we discover this celestial pulsar. Here we have used the decision tree under the new machine learning in this research. We use two classification techniques C4.5 Tree and classification and regression tree CART to classify the HTRU2 dataset and we set a model C4.5 Tree and CART from the ensemble of the classification and regression tree. The Model Ensemble C4.5 Tree and CART provides the best performance compared to the individual models of each classifier. Ensemble Model is useful for classifying candidates in pulsar and non-pulsar.

Key-Words / Index Term

Classification, C4.5, CART, Ensemble Model, HTRU2

References

[1] S. K. Saha, S. Sarkar, and P. Mitra, “Feature selection techniques for maximum entropy based biomedical named entity recognition,” J. Biomed. Inform., vol. 42, no. 5, pp. 905–911, 2009.
[2] P. S. Ramkumar and a. a. Deshpande, “Real-time signal processor for pulsar studies,” J. Astrophys. Astron., vol. 22, no. 4, pp. 321–342, 2001.
[3] E. Alpayd?n, “Introduction to machine learning,” Methods Mol. Biol., vol. 1107, pp. 105–128, 2014.
[4] R. J. Lyon, “WHY ARE PULSARS HARD TO FIND??,” 2016.
[5] R. J. Lyon, B. W. Stappers, S. Cooper, J. M. Brooke, and J. D. Knowles, “Fifty Years of Pulsar Candidate Selection?: From simple filters to a new principled real-time classification approach,” vol. 22, no. March, pp. 1–22, 2016.
[6] M. J. Keith et al., “The High Time Resolution Universe Pulsar Survey – I . System configuration and initial discoveries Introduction simulation and survey strategy,” vol. 627, pp. 619–627, 2010.
[7] Sivanandam and Deepa, Principles of Soft Computing, Second. wiley, 2014.
[8] A. Pujari, Data mining techniques, Third. University press, 2013.
[9] J. Han, M. Kamber, and J. Pei, Data mining: concepts and techniques, Third. Elsevier, 2012.
[10] S. Haykin, Neural Networks and Learning Machines, vol. 3. 2008.
[11] R. Lyon, “HTRU2,” 2016. [Online]. Available: https://figshare.com/articles/HTRU2/3080389/1. [Accessed: 01-Dec-2017].