An Efficient Framework for Improving Accuracy in Sports Analysis Using Logistic Regression Algorithm Compared With Naive Bayes Algorithm

Y. Rajesh; G. Sindhu

doi:10.1063/5.0177011

An Efficient Framework for Improving Accuracy in Sports Analysis Using Logistic Regression Algorithm Compared With Naive Bayes Algorithm

Y. Rajesh
, G. Sindhu^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

To improve the precision level of sports examination utilizing the Logistic Regression calculation and its exhibition is contrasted with the Naive Bayes calculation. Sports investigation was finished utilizing Naive Bayes with test size=10 and Logistic Regression calculation with test size=10 with 95% certainty span and pretest force of 80% was iterated at various times for anticipating the precision level of sports treatment of Football. The Logistic Regression calculation (91.87%) seemed to perform better compared to the Naive Bayes calculation (76.23%). The factual importance contrast 0.01 (p<0.05 Independent Sample T-Test) esteem expresses that the outcomes in the review are critical. Calculated Regression calculation demonstrates with better anticipating exactness rate for projection of sports examination of Football.

Original language	English
Title of host publication	AIP Conference Proceedings
Editors	Abhishek Dasore, Upendra Rajak, Manoj Panchal, Bukke Kiran Naik, Konijeti RamaKrishna
Publisher	American Institute of Physics Inc.
Edition	1
ISBN (Electronic)	9780735447356
DOIs	https://doi.org/10.1063/5.0177011
State	Published - 21 Nov 2023
Externally published	Yes
Event	1st International Conference on Contemporary Innovations in Mechanical Engineering, CIME 2022 - Nandyal City, India Duration: 22 Apr 2022 → 23 Apr 2022

Publication series

Name	AIP Conference Proceedings
Number	1
Volume	2821
ISSN (Print)	0094-243X
ISSN (Electronic)	1551-7616

Conference

Conference	1st International Conference on Contemporary Innovations in Mechanical Engineering, CIME 2022
Country/Territory	India
City	Nandyal City
Period	22/04/22 → 23/04/22

Bibliographical note

Publisher Copyright:
© 2023 American Institute of Physics Inc.. All rights reserved.

Keywords

Accuracy
Football
Machine Learning
Naive Bayes Algorithm
Novel Logistic Regression Algorithm
Sports Analysis

ASJC Scopus subject areas

General Physics and Astronomy

Access to Document

10.1063/5.0177011

Cite this

Rajesh, Y., & Sindhu, G. (2023). An Efficient Framework for Improving Accuracy in Sports Analysis Using Logistic Regression Algorithm Compared With Naive Bayes Algorithm. In A. Dasore, U. Rajak, M. Panchal, B. K. Naik, & K. RamaKrishna (Eds.), AIP Conference Proceedings (1 ed.). Article 020010 (AIP Conference Proceedings; Vol. 2821, No. 1). American Institute of Physics Inc.. https://doi.org/10.1063/5.0177011

Rajesh, Y. ; Sindhu, G. / An Efficient Framework for Improving Accuracy in Sports Analysis Using Logistic Regression Algorithm Compared With Naive Bayes Algorithm. AIP Conference Proceedings. editor / Abhishek Dasore ; Upendra Rajak ; Manoj Panchal ; Bukke Kiran Naik ; Konijeti RamaKrishna. 1. ed. American Institute of Physics Inc., 2023. (AIP Conference Proceedings; 1).

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title = "An Efficient Framework for Improving Accuracy in Sports Analysis Using Logistic Regression Algorithm Compared With Naive Bayes Algorithm",

abstract = "To improve the precision level of sports examination utilizing the Logistic Regression calculation and its exhibition is contrasted with the Naive Bayes calculation. Sports investigation was finished utilizing Naive Bayes with test size=10 and Logistic Regression calculation with test size=10 with 95\% certainty span and pretest force of 80\% was iterated at various times for anticipating the precision level of sports treatment of Football. The Logistic Regression calculation (91.87\%) seemed to perform better compared to the Naive Bayes calculation (76.23\%). The factual importance contrast 0.01 (p<0.05 Independent Sample T-Test) esteem expresses that the outcomes in the review are critical. Calculated Regression calculation demonstrates with better anticipating exactness rate for projection of sports examination of Football.",

keywords = "Accuracy, Football, Machine Learning, Naive Bayes Algorithm, Novel Logistic Regression Algorithm, Sports Analysis",

author = "Y. Rajesh and G. Sindhu",

note = "Publisher Copyright: {\textcopyright} 2023 American Institute of Physics Inc.. All rights reserved.; 1st International Conference on Contemporary Innovations in Mechanical Engineering, CIME 2022 ; Conference date: 22-04-2022 Through 23-04-2022",

year = "2023",

month = nov,

day = "21",

doi = "10.1063/5.0177011",

language = "English",

series = "AIP Conference Proceedings",

publisher = "American Institute of Physics Inc.",

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Rajesh, Y & Sindhu, G 2023, An Efficient Framework for Improving Accuracy in Sports Analysis Using Logistic Regression Algorithm Compared With Naive Bayes Algorithm. in A Dasore, U Rajak, M Panchal, BK Naik & K RamaKrishna (eds), AIP Conference Proceedings. 1 edn, 020010, AIP Conference Proceedings, no. 1, vol. 2821, American Institute of Physics Inc., 1st International Conference on Contemporary Innovations in Mechanical Engineering, CIME 2022, Nandyal City, India, 22/04/22. https://doi.org/10.1063/5.0177011

An Efficient Framework for Improving Accuracy in Sports Analysis Using Logistic Regression Algorithm Compared With Naive Bayes Algorithm. / Rajesh, Y.; Sindhu, G.
AIP Conference Proceedings. ed. / Abhishek Dasore; Upendra Rajak; Manoj Panchal; Bukke Kiran Naik; Konijeti RamaKrishna. 1. ed. American Institute of Physics Inc., 2023. 020010 (AIP Conference Proceedings; Vol. 2821, No. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - An Efficient Framework for Improving Accuracy in Sports Analysis Using Logistic Regression Algorithm Compared With Naive Bayes Algorithm

AU - Rajesh, Y.

AU - Sindhu, G.

PY - 2023/11/21

Y1 - 2023/11/21

N2 - To improve the precision level of sports examination utilizing the Logistic Regression calculation and its exhibition is contrasted with the Naive Bayes calculation. Sports investigation was finished utilizing Naive Bayes with test size=10 and Logistic Regression calculation with test size=10 with 95% certainty span and pretest force of 80% was iterated at various times for anticipating the precision level of sports treatment of Football. The Logistic Regression calculation (91.87%) seemed to perform better compared to the Naive Bayes calculation (76.23%). The factual importance contrast 0.01 (p<0.05 Independent Sample T-Test) esteem expresses that the outcomes in the review are critical. Calculated Regression calculation demonstrates with better anticipating exactness rate for projection of sports examination of Football.

AB - To improve the precision level of sports examination utilizing the Logistic Regression calculation and its exhibition is contrasted with the Naive Bayes calculation. Sports investigation was finished utilizing Naive Bayes with test size=10 and Logistic Regression calculation with test size=10 with 95% certainty span and pretest force of 80% was iterated at various times for anticipating the precision level of sports treatment of Football. The Logistic Regression calculation (91.87%) seemed to perform better compared to the Naive Bayes calculation (76.23%). The factual importance contrast 0.01 (p<0.05 Independent Sample T-Test) esteem expresses that the outcomes in the review are critical. Calculated Regression calculation demonstrates with better anticipating exactness rate for projection of sports examination of Football.

KW - Accuracy

KW - Football

KW - Machine Learning

KW - Naive Bayes Algorithm

KW - Novel Logistic Regression Algorithm

KW - Sports Analysis

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AN - SCOPUS:85179833968

T3 - AIP Conference Proceedings

BT - AIP Conference Proceedings

A2 - Dasore, Abhishek

A2 - Rajak, Upendra

A2 - Panchal, Manoj

A2 - Naik, Bukke Kiran

A2 - RamaKrishna, Konijeti

PB - American Institute of Physics Inc.

T2 - 1st International Conference on Contemporary Innovations in Mechanical Engineering, CIME 2022

Y2 - 22 April 2022 through 23 April 2022

ER -

An Efficient Framework for Improving Accuracy in Sports Analysis Using Logistic Regression Algorithm Compared With Naive Bayes Algorithm

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this