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Reseach Article

Astrological Prediction for Profession Doctor using Classification Techniques of Artificial Intelligence

by Neelam Chaplot, Praveen Dhyani, O. P. Rishi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 122 - Number 15
Year of Publication: 2015
Authors: Neelam Chaplot, Praveen Dhyani, O. P. Rishi
10.5120/21778-5052

Neelam Chaplot, Praveen Dhyani, O. P. Rishi . Astrological Prediction for Profession Doctor using Classification Techniques of Artificial Intelligence. International Journal of Computer Applications. 122, 15 ( July 2015), 28-31. DOI=10.5120/21778-5052

@article{ 10.5120/21778-5052,
author = { Neelam Chaplot, Praveen Dhyani, O. P. Rishi },
title = { Astrological Prediction for Profession Doctor using Classification Techniques of Artificial Intelligence },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 122 },
number = { 15 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 28-31 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume122/number15/21778-5052/ },
doi = { 10.5120/21778-5052 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:10:39.205835+05:30
%A Neelam Chaplot
%A Praveen Dhyani
%A O. P. Rishi
%T Astrological Prediction for Profession Doctor using Classification Techniques of Artificial Intelligence
%J International Journal of Computer Applications
%@ 0975-8887
%V 122
%N 15
%P 28-31
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Astrology can be an interesting example of the application of various classification techniques of artificial intelligence. In astrology, predictions about different aspects of human life are done based on the planetary position of the stars at the time of birth of a person. In this research work, the positions of the planets and stars at the time of the birth of a person are utilized. This information is used to predict the possibility of person to become doctor. Total 102 records were collected for the study out of that half of the records were of persons that were doctor and other half records of the persons that were not doctor by profession. Thereafter, various supervised classification techniques such as Logistic, Naïve Bayes, Simple Cart, Decision Stump, Decision Table and DTNB algorithm were used and results were compared for their accuracy.

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Index Terms

Computer Science
Information Sciences

Keywords

Artificial Intelligence Astrological Prediction Classification Techniques Prediction of Profession Doctor Weka.