Best 11 selection using machine learning
This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.
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BRAC University
2018
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| Dostęp online: | http://hdl.handle.net/10361/10181 |
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10361-101812022-01-26T10:15:52Z Best 11 selection using machine learning Anik, Aminul Islam Yeaser, Sakif Hossain, A.G.M. Imam Chakrabarty, Amitabha Department of Computer Science and Engineering, BRAC University Cricket Machine learning Best 11 selection This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018. Cataloged from PDF version of thesis. Includes bibliographical references. Cricket has become the most popular game not only in Bangladesh but also around the world. Day by day it is gaining more people’s attention. The name and glory of team Bangladesh has trespassed the country’s border and it is creating a huge impact in the world cricket. To make sure the continuous development of the team, a more professional approach and help from IT sector is needed. Remembering this fact, we used machine learning to select the best players from the standby list based on the previous playing statistics and then from that players we have found out the winning team combination. We have collected the data from websites that offers trustable sports statistics. Feature selection algorithms like Recursive feature elimination and univariate selection are used to find out the attributes that are more related to the output feature. Machine learning Algorithms such as linear regression, support vector machine with linear and polynomial kernel was used to predict the runs scored by a batsman and runs given by a bowler. Later on, we have also used fully connected neural network to find out the performance comparison of different algorithm. We have selected the players for the team according to their performances and experiences. Our goal was to form a well-balanced team through our approach. Aminul Islam Anik Sakif Yeaser A.G.M. Imam Hossain B. Computer Science and Engineering 2018-05-21T07:53:49Z 2018-05-21T07:53:49Z 2018 2018-04 Thesis ID 14301039 ID 14301045 ID 14301046 http://hdl.handle.net/10361/10181 en BRAC University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 44 pages application/pdf BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Cricket Machine learning Best 11 selection |
| spellingShingle |
Cricket Machine learning Best 11 selection Anik, Aminul Islam Yeaser, Sakif Hossain, A.G.M. Imam Best 11 selection using machine learning |
| description |
This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018. |
| author2 |
Chakrabarty, Amitabha |
| author_facet |
Chakrabarty, Amitabha Anik, Aminul Islam Yeaser, Sakif Hossain, A.G.M. Imam |
| format |
Thesis |
| author |
Anik, Aminul Islam Yeaser, Sakif Hossain, A.G.M. Imam |
| author_sort |
Anik, Aminul Islam |
| title |
Best 11 selection using machine learning |
| title_short |
Best 11 selection using machine learning |
| title_full |
Best 11 selection using machine learning |
| title_fullStr |
Best 11 selection using machine learning |
| title_full_unstemmed |
Best 11 selection using machine learning |
| title_sort |
best 11 selection using machine learning |
| publisher |
BRAC University |
| publishDate |
2018 |
| url |
http://hdl.handle.net/10361/10181 |
| work_keys_str_mv |
AT anikaminulislam best11selectionusingmachinelearning AT yeasersakif best11selectionusingmachinelearning AT hossainagmimam best11selectionusingmachinelearning |
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