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Implementation and Analysis of the Performance of EDTA (Enhanced Decision Tree Data Mining Algorithm) for diagnosis of Angioplasty and Stents for Heart Disease Treatment

Amarjeet Kaur1 , Ashok Jetawat22 , Gurpreet Singh3

  1. COMPUTER SCIENCE& ENGG, PACIFIC UNIVERSITY, UDAIPUR, INDIA.
  2. COMPUTER SCIENCE& ENGG, Pacific University, Udaipur, India.
  3. COMPUTER SCIENCE& ENGG, ST.Soldier Institute Of Engg & Tech, Jalandhar, India.

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-4 , Page no. 541-543, Apr-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i4.541543

Online published on Apr 30, 2018

Copyright © Amarjeet Kaur, Ashok Jetawat2, Gurpreet Singh . 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.

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IEEE Style Citation: Amarjeet Kaur, Ashok Jetawat2, Gurpreet Singh, “Implementation and Analysis of the Performance of EDTA (Enhanced Decision Tree Data Mining Algorithm) for diagnosis of Angioplasty and Stents for Heart Disease Treatment,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.541-543, 2018.

MLA Style Citation: Amarjeet Kaur, Ashok Jetawat2, Gurpreet Singh "Implementation and Analysis of the Performance of EDTA (Enhanced Decision Tree Data Mining Algorithm) for diagnosis of Angioplasty and Stents for Heart Disease Treatment." International Journal of Computer Sciences and Engineering 6.4 (2018): 541-543.

APA Style Citation: Amarjeet Kaur, Ashok Jetawat2, Gurpreet Singh, (2018). Implementation and Analysis of the Performance of EDTA (Enhanced Decision Tree Data Mining Algorithm) for diagnosis of Angioplasty and Stents for Heart Disease Treatment. International Journal of Computer Sciences and Engineering, 6(4), 541-543.

BibTex Style Citation:
@article{Kaur_2018,
author = {Amarjeet Kaur, Ashok Jetawat2, Gurpreet Singh},
title = {Implementation and Analysis of the Performance of EDTA (Enhanced Decision Tree Data Mining Algorithm) for diagnosis of Angioplasty and Stents for Heart Disease Treatment},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2018},
volume = {6},
Issue = {4},
month = {4},
year = {2018},
issn = {2347-2693},
pages = {541-543},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1897},
doi = {https://doi.org/10.26438/ijcse/v6i4.541543}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i4.541543}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1897
TI - Implementation and Analysis of the Performance of EDTA (Enhanced Decision Tree Data Mining Algorithm) for diagnosis of Angioplasty and Stents for Heart Disease Treatment
T2 - International Journal of Computer Sciences and Engineering
AU - Amarjeet Kaur, Ashok Jetawat2, Gurpreet Singh
PY - 2018
DA - 2018/04/30
PB - IJCSE, Indore, INDIA
SP - 541-543
IS - 4
VL - 6
SN - 2347-2693
ER -

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Abstract

Data mining is a process of extraction of useful information and patterns from huge data. It is also called as knowledge discovery process, knowledge mining from data, knowledge extraction or data pattern analysis. We present a improved approach to support nearest neighbor queries from mobile hosts by leveraging the sharing capabilities of wireless ad-hoc networks. We illustrate how previous query results cached in the local storage of neighboring mobile peers can be leveraged to either fully or partially compute and verify spatial queries at a local host. The feasibility and appeal of our technique is illustrated through extensive simulation results that indicate a considerable reduction of the query load on the remote database.

Key-Words / Index Term

Mobile Services, CART, C45, EDTA

References

[1] Xiang Lian, Student Member, IEEE, and Lei Chen, Member, IEEE, “Ranked Query Processing in Uncertain Databases”, IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 22, NO.3, MARCH 2010.
[2] Stavroula G. Mougiakakou, Member, IEEE, “SMARTDIAB: A Communication and Information Technology Approach for the Intelligent Monitoring, Management and ollow-up of Type 1 Diabetes Patients”, IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE, VOL. 14, NO. 3, MAY 2010.
[3] Eric Hsueh-Chan Lu, Vincent S. Tseng, Member, IEEE, “Mining Cluster-Based Temporal Mobile Sequential Patterns in Location-Based Service Environments” , IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 23, NO. 6, JUNE 2011.
[4] Mark N. Gasson, EleniKosta, Denis Royer, Martin Meints, and Kevin Warwick, “Normality Mining: Privacy Implications of Behavioral Profiles Drawn From GPS Enabled Mobile Phones”, IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART C: APPLICATIONS AND REVIEWS, VOL. 41, NO. 2, MARCH 2011.
[5] Tzung-Shi Chen, Member, IEEE, Yen-Ssu Chou, and Tzung-Cheng Chen, “Mining User Movement Behavior Patterns in a Mobile Service Environment”, IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART A: SYSTEMS AND HUMANS, VOL. 42, NO. 1, JANUARY 2012.
[6] R.Agrawal, T. Imielinski, and A. Swami, “Mining Associationsbetween Sets of Items in Massive Databases,” Proc. ACMSIGMOD, pp. 207-216, May 1993.
[7] R.Agrawal and J. Shafer, “Parallel Mining of Association Rules,”IEEE Trans. Knowledge and Data Eng, vol. 8, no. 6, pp. 866-883, Dec.1996.
[8] R.Agrawal and R. Srikant, “Mining Sequential Patterns,” Proc.11th Int’l Conf. Data Eng., pp. 3-14, Mar. 1995.