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Discriminant Analysis of Sports Personalities for Predicting Better Performance

by Namrata Bhawsar, Santosh K. Vishwakarma
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 180 - Number 13
Year of Publication: 2018
Authors: Namrata Bhawsar, Santosh K. Vishwakarma
10.5120/ijca2018916247

Namrata Bhawsar, Santosh K. Vishwakarma . Discriminant Analysis of Sports Personalities for Predicting Better Performance. International Journal of Computer Applications. 180, 13 ( Jan 2018), 1-6. DOI=10.5120/ijca2018916247

@article{ 10.5120/ijca2018916247,
author = { Namrata Bhawsar, Santosh K. Vishwakarma },
title = { Discriminant Analysis of Sports Personalities for Predicting Better Performance },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2018 },
volume = { 180 },
number = { 13 },
month = { Jan },
year = { 2018 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume180/number13/28919-2018916247/ },
doi = { 10.5120/ijca2018916247 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:00:32.505665+05:30
%A Namrata Bhawsar
%A Santosh K. Vishwakarma
%T Discriminant Analysis of Sports Personalities for Predicting Better Performance
%J International Journal of Computer Applications
%@ 0975-8887
%V 180
%N 13
%P 1-6
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Managing huge amount of data has always been a matter of concern. With the increasing growth in the sports domain, the amount of data in sports academy is also increasing. In this paper, Discriminant Analysis is used as a means of analyzing the effect of independent variables upon the dependent variables. Discriminant analysis is a method of data mining and it also has the ability to predict the category and class to which the focus belongs. With the help of this method, one can predict the performance of an athlete that can help the sportsperson and the trainer to choose their desired prime sport. The dataset used in the research is the battery test of athletes conducted in the sports academy. RapidMiner, an open source software is used to fetch results.

References
  1. Han, J., Kamber, M., Pei, J.. Data Mining: Concepts and Techniques. The Morgan Kaufmann Series in Data Management Systems. Morgan Kaufmann; 3rd ed.; 2012. ISBN 978-0-12- 381479-1.
  2. Pujari, K., A.. Data Mining Techniques. ISBN-10:8173713804.
  3. Badr, G., Algobail, A., Almutairi, H., Almutery, M., Predicting Students Performance in University Courses: A Case Study and Tool in KSU Mathematics Department. Procedia Computer Science 82 ( 2016 ) 80 89.
  4. Shahiri,A., M., Husain,W., Rashid,N.,A., A Review on Predicting Students Performance using Data Mining Techniques. Procedia Computer Science 72 ( 2015 ) 414 422.
  5. RapidminerStudioDocumentation http://docs.rapidminer.com/studio/
  6. Predicting Consumer Purchase Intention: A Discriminant Analysis Approach Sougata Banerjee Sarwat Pawar
  7. www.google.co.in/
Index Terms

Computer Science
Information Sciences

Keywords

Data Mining Knowledge Discovery in Databases(KDD) Linear Discriminant Analysis(LDA) Classification Athlete’s Performance Prediction.

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