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Machine learning and Systems Approaches in Relation of Helicobacter pylori To Ageing Diseases

D. Santosh Kumari1 , DSVGK Kaladhar2

Section:Research Paper, Product Type: Journal Paper
Volume-07 , Issue-03 , Page no. 202-205, Feb-2019

Online published on Feb 15, 2019

Copyright © D. Santosh Kumari, DSVGK Kaladhar . 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: D. Santosh Kumari, DSVGK Kaladhar, “Machine learning and Systems Approaches in Relation of Helicobacter pylori To Ageing Diseases,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.03, pp.202-205, 2019.

MLA Style Citation: D. Santosh Kumari, DSVGK Kaladhar "Machine learning and Systems Approaches in Relation of Helicobacter pylori To Ageing Diseases." International Journal of Computer Sciences and Engineering 07.03 (2019): 202-205.

APA Style Citation: D. Santosh Kumari, DSVGK Kaladhar, (2019). Machine learning and Systems Approaches in Relation of Helicobacter pylori To Ageing Diseases. International Journal of Computer Sciences and Engineering, 07(03), 202-205.

BibTex Style Citation:
@article{Kumari_2019,
author = {D. Santosh Kumari, DSVGK Kaladhar},
title = {Machine learning and Systems Approaches in Relation of Helicobacter pylori To Ageing Diseases},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {2 2019},
volume = {07},
Issue = {03},
month = {2},
year = {2019},
issn = {2347-2693},
pages = {202-205},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=708},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=708
TI - Machine learning and Systems Approaches in Relation of Helicobacter pylori To Ageing Diseases
T2 - International Journal of Computer Sciences and Engineering
AU - D. Santosh Kumari, DSVGK Kaladhar
PY - 2019
DA - 2019/02/15
PB - IJCSE, Indore, INDIA
SP - 202-205
IS - 03
VL - 07
SN - 2347-2693
ER -

           

Abstract

Helicobacter pylori is one of the bacterial pathogen showing great effect and associations with ageing diseases. The complex data prediction was done with Weka software. When compared with data distribution between Males and Females in relation with class H.pylori, it is shown that females are more prone to ageing diseases (especially gastric and Obesity). Cluster Centroids method was predicted with more chances for people in Urban regions with family history suffers gastric, expiry due to heart stoke with gastric, drink tea, with tension and stress. AD Tree shown positive for H.pylori (N) showing stomach pain, family suffered previously and Age >29.5. Subset Evaluator method was shown that Stomach pain, Aging diseases and smoking are the attributes associated with H.pylori. The highest accuracy for the data was predicted with random Forest and K Star followed by J48, Bayes Net, Naive Bayes, LMT and Simple Cost.

Key-Words / Index Term

Helicobacter pylori, Ageing diseases, Systems approaches, Machine learning

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