Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/115
Title: An Application of Linear Regression & Artificial Neural Network Model in the NFL Result Prediction
Authors: Anyama, Oscar Uzoma
Igiri, Chinwe Peace
Keywords: ANN; Hybrid; Machine learning; Models; Prediction
Issue Date: Jan-2015
Publisher: International Journal of Engineering Research & Technology (IJERT)
Citation: igiri, C. P. (2015). An Application of Linear Regression & Artificial Neural Network Model in the NFL Result Prediction. International Journal of Engineering Research & Technology (IJERT) ISSN: 2278-0181 IJERTV4IS010426 www.ijert.org
Series/Report no.: 4;1
Abstract: Football results prediction has gained popularity in recent years. Nonhybrid approaches have shown complex and low prediction results. Data mining tools with insufficient features, however, have also yielded low predictions. In our research, machine learning has been used to develop a hybrid football match result predictive model for NFL. We constructed a more comprehensive system with improved prediction accuracy by using a hybridized approach. Our prediction system for football match results was implemented using a hybrid of artificial neural network (ANN) and linear regression (LR) techniques with Rapid Miner as a data mining tool. The technique yielded 90.32% prediction accuracy. With this output, it is observed that the prediction accuracy is higher than those of existing systems.
URI: http://localhost:8080/xmlui/handle/123456789/115
Appears in Collections:Computer Science



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.