Machine learning as a tool to predict NBA playoff outcomes
DOI:
https://doi.org/10.47611/jsrhs.v13i1.6007Keywords:
Machine Learning, Supervised Learning, Logistic Regression, Binary Classfication Problem, NBA StatisticsAbstract
Machine learning is the field of computer science that uses data to make predictions and decisions. The problem we consider in this article belongs to the class known as supervised learning and the technique we use is logistic regression. After explaining supervised learning and logistic regression, we use a data set to develop a computational model able to predict the outcome of an NBA playoff game.
Downloads
References or Bibliography
Andriy Burkov. The hundred-page machine learning book, volume 1. Andriy Burkov Canada,
Jerome Friedman, Trevor Hastie, Robert Tibshirani, et al. The elements of statistical
learning, volume 1. Springer series in statistics New York, 2001.
Tom M Mitchell et al. Machine learning. 1997.
Toby Segaran. Programming collective intelligence: building smart web 2.0 applications. ”
O’Reilly Media, Inc.”, 2007.
Published
How to Cite
Issue
Section
Copyright (c) 2024 Benjamin Wang
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Copyright holder(s) granted JSR a perpetual, non-exclusive license to distriute & display this article.
