Comparing machine learning and ensemble learning in the field of football

Title

Comparing machine learning and ensemble learning in the field of football

Creator

Khan S.; Kirubanand V.B.

Description

Football has been one of the most popular and loved sports since its birth on November 6th, 1869. The main reason for this is because it is highly unpredictable in nature. Predicting football matches results seems like the perfect problem for machine learning models. But there are various caveats such as picking the right features from an enormous number of available features. There have been many models which have been applied to various football-related datasets. This paper aims to compare Support Vector Machines a machine learning model and XGBoost an Ensemble learning model and how Ensemble Learning can greatly improve the accuracy of the predictions. Copyright 2019 Institute of Advanced Engineering and Science. All rights reserved.

Source

International Journal of Electrical and Computer Engineering, Vol-9, No. 5, pp. 4321-4325.

Date

2019-01-01

Publisher

Institute of Advanced Engineering and Science

Subject

Decision trees; Ensemble learning; Prescision; Support vector machines; XGBoost

Coverage

Khan S., Department of Computer Science, CHRIST (Deemed to Be University), Hosur Main Road, Bengaluru, Karnataka, 560029, India; Kirubanand V.B., Department of Computer Science, CHRIST (Deemed to Be University), Hosur Main Road, Bengaluru, Karnataka, 560029, India

Rights

All Open Access; Gold Open Access; Green Open Access

Relation

ISSN: 20888708

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.11591/ijece.v9i5.pp4321-4325

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067626731&doi=10.11591%2fijece.v9i5.pp4321-4325&partnerID=40&md5=27076f34d35c23322221fc469d6012fd