Performance analysis of various features and functions settings
on the neural network accuracy

a 2022

Performance analysis of various features and functions settings on the neural network accuracy

BOZDĚCH, Michal

Basic information

Original name

Performance analysis of various features and functions settings on the neural network accuracy

Authors

BOZDĚCH, Michal (203 Czech Republic, guarantor, belonging to the institution)

Edition

-13th INTERNATIONAL CONFERENCE ON KINANTHROPOLOGY "Sport and Quality of Life". 2022

Other information

Language

English

Type of outcome

Konferenční abstrakt

Field of Study

50902 Social sciences, interdisciplinary

Country of publisher

Czech Republic

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

13th INTERNATIONAL CONFERENCE ON KINANTHROPOLOGY "Sport and Quality of Life"

RIV identification code

RIV/00216224:14510/22:00130440

Organization unit

Faculty of Sports Studies

ISBN

978-80-280-0107-0

Keywords in English

ANN; DNN; inputs and outputs selection and extraction; hidden/output layer activation function; optimization algorithm

Změněno: 31/10/2023 09:43, Mgr. Michal Bozděch, Ph.D.

Abstract

V originále

Artificial intelligence with machine learning (more precisely neural network) is one of the most used types of an algorithm, in sports but also in general. In the past, only wealthier sports clubs could afford to use her potential. With the development of affordable software, the situation changes and every club can use it to their advantage, but there is a problem with how to prepare data and how to set up the algorithm. For these reasons, this study aims to determine whether features or function settings have a greater effect on model accuracy. An initial feature dataset (n = 18,882; 1,929 players, 8 variables) was created from publicly available sources. Each of the 6 feature settings consisted of 96 independent models. A total of 384 models were created, in which their accuracy (in the training and testing phases) and the percentage difference between the training and testing phases were further analysed. No statistically significant differences were found between the accuracy of the function’s settings, but statistically significant differences were confirmed between the features settings, of which14 models with 100% accuracy and 1.00 AUC. From this study, it is clear that feature settings, especially the reduction of the number of outputs, are a more important factor in increasing the accuracy of the artificial intelligence model and that variables Weight, Height, and Age had the highest frequency of occurrences of normalized importance and can therefore be identified as one of the most important features for prediction of final rank.

Citovat

BOZDĚCH, Michal. Performance analysis of various features and functions settings on the neural network accuracy. In -13th INTERNATIONAL CONFERENCE ON KINANTHROPOLOGY "Sport and Quality of Life". 2022. ISBN 978-80-280-0107-0.

@proceedings{2267059,
   author = {Bozděch, Michal},
   booktitle = {-13th INTERNATIONAL CONFERENCE ON KINANTHROPOLOGY "Sport and Quality of Life".},
   keywords = {ANN; DNN; inputs and outputs selection and extraction; hidden/output layer activation function; optimization algorithm},
   language = {eng},
   isbn = {978-80-280-0107-0},
   title = {Performance analysis of various features and functions settings on the neural network accuracy},
   url = {https://conference.fsps.muni.cz/},
   year = {2022}
}

TY  - CONF
ID  - 2267059
AU  - Bozděch, Michal
PY  - 2022
TI  - Performance analysis of various features and functions settings on the neural network accuracy
SN  - 9788028001070
KW  - ANN
KW  - DNN
KW  - inputs and outputs selection and extraction
KW  - hidden/output layer activation function
KW  - optimization algorithm
UR  - https://conference.fsps.muni.cz/
N2  - Artificial intelligence with machine learning (more precisely neural network) is one of the most used types of an algorithm, in sports but also in general. In the past, only wealthier sports clubs could afford to use her potential. With the development of affordable software, the situation changes and every club can use it to their advantage, but there is a problem with how to prepare data and how to set up the algorithm. For these reasons, this study aims to determine whether features or function settings have a greater effect on model accuracy. An initial feature dataset (n = 18,882; 1,929 players, 8 variables) was created from publicly available sources. Each of the 6 feature settings consisted of 96 independent models. A total of 384 models were created, in which their accuracy (in the training and testing phases) and the percentage difference between the training and testing phases were further analysed. No statistically significant differences were found between the accuracy of the function’s settings, but statistically significant differences were confirmed between the features settings, of which14 models with 100% accuracy and 1.00 AUC. From this study, it is clear that feature settings, especially the reduction of the number of outputs, are a more important factor in increasing the accuracy of the artificial intelligence model and that variables Weight, Height, and Age had the highest frequency of occurrences of normalized importance and can therefore be identified as one of the most important features for prediction of final rank.
ER  -

BOZDĚCH, Michal. Performance analysis of various features and functions settings on the neural network accuracy. In \textit{-13th INTERNATIONAL CONFERENCE ON KINANTHROPOLOGY ''Sport and Quality of Life''.}. 2022. ISBN~978-80-280-0107-0.

Detailed Information on Publication Record