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Cricket World Cup Predictions Using KNN Intelligent Bigdata Approach

Published: 08 September 2018 Publication History

Abstract

In May 2019, the ICC 2019 Cricket World Cup is the 12th edition of the cricket World Cup and is scheduled to be hosted by England and Wales. This research work is trying to predict the winner of the 12th version of ICC world cup using intelligent KNN Bigdata approach. Our chosen machine learning namely the KNN (K Nearest Neighbor Algorithm) and data reduction algorithm will be presented. Additionally, the steps taken to achieve the KNN classifications as applied to all datasets in detail. KNN and R Language will be defined in depth. It will also be mentioned how and why they apply to this project. The selected datasets required cleaning and cleansing and it is done using MySQL to ensure that they are ready to have the KNN algorithm applied to them. Finally, the crux of this paper, the application of the KNN algorithm will be discussed in detail as they are applied to the datasets. This research work, the concepts of Bigdata will be used to predict the winner of the 2019 ICC Cricket World Cup.

References

[1]
https://www.smartdatacollective.com/what-big-data-and-how-useful-it/. {Accessed April 2018}.
[2]
https://www.sas.com/en_za/insights/analytics/machine-learning.html. {Accessed April 2018}.
[3]
A. Aburas, Machine Learning Algorithms for Big Data Project, Durban: University of Kwa-Zulu Natal, 2018.
[4]
http://www.saedsayad.com/k_nearest_neighbors.htm. {Accessed 15 April 2018}.
[5]
https://www.rdocumentation.org/packages/clusterSim/versions/0.47-1/topics/data.Normalization. {Accessed April 2018}
[6]
https://www.kaggle.com/datasets. {Accessed April 2018}.
[7]
https://www.r-project.org/about.html. {Accessed April 2018}.
[8]
https://www.quora.com/What-is-XAMPP-and-how-to-use-it. {Accessed April 2018}.
[9]
http://www.saedsayad.com/k_nearest_neighbours.html. {Accessed April 2018}.
[10]
https://www.webopedia.com/TERM/E/entity_relationship_diagram.html. {Accessed March 2018}.
[11]
http://stats.espncricinfo.com/ci/engine/stats/index.html. {Accessed April 2018}.
[12]
https://www.icc-cricket.com/ {Accessed April 2018}.
[13]
https://www.icc-cricket.com/cricket-world-cup {Accessed May 2018}.
[14]
M. Minelli, M. Chambers, A. Dhiraj, Big Data, Big Analytics: Emerging Busi- ness Intelligence and Analytic Trends for Today's Businesses (Wiley CIO), 1st edition, Wiley Publishing, 2013.
[15]
M. Minelli, M. Chambers, A. Dhiraj, Big Data, Big Analytics: Emerging Busi- ness Intelligence and Analytic Trends for Today's Businesses (Wiley CIO), 1st edition, Wiley Publishing, 2013.
[16]
T.M. Cover, P.E. Hart, nearest neighbour pattern classification, IEEE Trans. Inf. Theory 13 (1) (1967) 21--27.
[17]
X. Wu, V. Kumar (Eds.), The Top Ten Algorithms in Data Mining, Chapman & Hall/CRC Data Mining and Knowledge Discovery, 2009.
[18]
C.P. Chen, C.-Y. Zhang, Data-intensive applications, challenges, techniques and technologies: a survey on big data, Inf. Sci. 275 (2014) 314--347.
[19]
Jesus Maillo, Sergio Ramírez, Isaac Triguero & Francisco Herrera, kNN-IS: An Iterative Spark-based design of the k-Nearest Neighbors classifier for big data, Knowledge-Based Systems 117 (2017) 3--15.
[20]
Memoona Khanum, Warda Imtiaz, Humaraia Abdul Ghafoor, Rabeea Sehar, A Survey on Unsupervised Machine Learning Algorithms for Automation, Classification and Maintenance, International Journal of Computer Applications (0975 - 8887) Volume 119 - No.13, June 2015.
[21]
Peter Dayan, Unsupervised Learning, Appeared in Wilson, RA & Keil, F, editors. The MIT Encyclopedia of the Cognitive Sciences, 1999.
[22]
Itamar Arel, Derek C. Rose, Thomas P. Karnowski, Deep machine learning - a new frontier in artificial intelligence research, IEEE Comput. Intell. Mag. 5 (4) (2010) 13--18.
[23]
Geoffrey E. Hinton, Simon Osindero, Yee-Whye Teh, A fast learning algorithm for deep belief nets, Neural Comput. 18 (2006) 1527--1554.
[24]
Dong Yu, Li Deng, Deep learning and its applications to signal and information processing, IEEE Signal Process. Mag. 28 (1) (2011) 145--154.
[25]
T.M. Cover, P.E. HartNearest neighbor pattern classification, IEEE Trans. Inf. Theory, 13 (1) (1967), pp. 21--27.
[26]
X. Wu, V. Kumar (Eds.)The Top Ten Algorithms in Data Mining, Chapman & Hall/CRC Data Mining and Knowledge Discovery (2009).
[27]
Y. Chen, E.K. Garcia, M.R. Gupta, A. Rahimi, L. CazzantiSimilarity-based classification: concepts and algorithms J. Mach. Learn. Res., 10 (2009), pp. 747--776.
[28]
Big Data Fundamentals: Concepts, Drivers, and Techniques, 2016, Thomas Erl, Wajid Khattak and Paul Buhler ISBN-10: 0134291077 • ISBN-13: 9780134291079.
[29]
https://www.apachefriends.org/index.html. {Accessed online May2018}
[30]
https://www.r-project.org/. {Accessed online May2018}
[31]
N. Bhatia and A. Vandana, "Survey of Nearest Neighbor Techniques," (IJCSIS) International Journal of Computer Science and Information Security, vol. 8, no. 2, pp. 302--305, 2010.
[32]
K. Q. Weinberger and L. K. Saul, "Distance Metric Learning for Large Margin Nearest Neighbor Classification," Journal of Machine Learning Research, vol. 10, pp. 207--244, 2009.
[33]
A. Kataria and M. D. Singh, "A Review of Data Classification Using K-Nearest Neighbour Algorithm," International Journal of Emerging Technology and Advanced Engineering, vol. 3, no. 6, pp. 354--360, 2013.
[34]
HAN J W, KAMBE M. Data Mining: Concepts and Techniques {M}. Fan Ming, Meng Xiaofeng, translated. Beijing: Mechanical Industry Press, 2001.
[35]
http://stats.espncricinfo.com/SouthAfrica/engine/records/team/series_results.html?class=2;id=6;type=team. {Accessed online May2018}
[36]
https://www.acru.ukzn.ac.za/~hippo/. {Accessed online May2018}
[37]
https://www.mysql.com/. {Accessed online April2018}
[38]
https://www.phpmyadmin.net/. {Accessed online April2018}

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Published In

cover image ACM Other conferences
ICCBD '18: Proceedings of the 2018 International Conference on Computing and Big Data
September 2018
103 pages
ISBN:9781450365406
DOI:10.1145/3277104
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 08 September 2018

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Author Tags

  1. Bigdata
  2. ICC
  3. KNN
  4. R language
  5. machine learning
  6. predict

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View all
  • (2024)PURP: A Scalable System for Predicting Short-Term Urban Traffic Flow Based on License Plate Recognition DataBig Data Mining and Analytics10.26599/BDMA.2023.90200177:1(171-187)Online publication date: Mar-2024
  • (2022)Applications of Machine Learning in cricket: A systematic reviewMachine Learning with Applications10.1016/j.mlwa.2022.10043510(100435)Online publication date: Dec-2022
  • (2021)Cricket Match Analytics Using the Big Data ApproachElectronics10.3390/electronics1019235010:19(2350)Online publication date: 26-Sep-2021
  • (2020)Extraction of Strong and Weak Regions of Cricket Batsman through Text-Commentary Analysis2020 IEEE 23rd International Multitopic Conference (INMIC)10.1109/INMIC50486.2020.9318089(1-6)Online publication date: 5-Nov-2020

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