DocumentCode
3026538
Title
Astrological prediction for profession using classification techniques of artificial intelligence
Author
Chaplot, Neelam ; Dhyani, Praveen ; Rishi, O.P.
Author_Institution
Dept. of Comput. Sci., Banasthali Univ., Banasthali, India
fYear
2015
fDate
15-16 May 2015
Firstpage
233
Lastpage
236
Abstract
Astrology has started around 4000 years back and has significantly developed over a period of time. Till date no unified rules or standards for astrological prediction exist in the world. Astrologers concentrate on providing quality services to persons rather than defining universal rules and standards for astrological prediction. Advances in artificial intelligence resulted in large number of applications for analysis and prediction. In these applications computer learn from unknown, large, noisy or complex data sets and perform prediction and classification of data. In this paper we are trying to find universal rules and validity of astrology using various scientific methods. In this paper we are going to predict profession of person using ZeroR, Simple Cart and Decision Table classification algorithm. The data set for learning classification consisted of 24 records of Singer, 24 records of Player and 10 records of Scientist. Weka tool[1] available under General public license is use to perform analysis and prediction task.
Keywords
artificial intelligence; pattern classification; prediction theory; Simple Cart; ZeroR; artificial intelligence; astrological prediction; astrology; classification techniques; data set; decision table classification algorithm; general public license; profession; universal rules; Accuracy; Algorithm design and analysis; Artificial intelligence; Automation; Classification algorithms; Data mining; Prediction algorithms; Artificial Intelligencet; Astrological Predection; Clasification; Machine Learning; Prediction of Profession;
fLanguage
English
Publisher
ieee
Conference_Titel
Computing, Communication & Automation (ICCCA), 2015 International Conference on
Conference_Location
Noida
Print_ISBN
978-1-4799-8889-1
Type
conf
DOI
10.1109/CCAA.2015.7148378
Filename
7148378
Link To Document