Document Type
Article
Publication Date
11-2019
Publication Title
International Journal of Economics and Management Studies
First Page
1
Last Page
3
DOI
10.14445/23939125/IJEMS-V6I11P101
Additional Publication URL
http://www.internationaljournalssrg.org/IJEMS/2019/Volume6-Issue11/IJEMS-V6I11P101.pdf
Abstract
A North American provider of vehicle parking solutions seeks to predict if a bid will be successful and, for those that are successful, what will be the cumulative sales revenue. Both traditional statistical methods and machine learning algorithms were employed. The machine learning techniques performed better than the statistical methods. There is no statistically significant difference between random forest and extreme gradient boosting for either the binary classification task or the regression task.
Rights
This article was originally published in International Journal of Economics and Management Studies, 2019, Volume 6, Issue 11.
The version of record is available at International Journal of Economics and Management Studies. Archived with permission from Blood Advances, all rights reserved.
Recommended Citation
King, Barry E. and Davidson, Jason, "Using Machine Learning to Predict Sales Conditional on Bid Acceptance" (2019). Scholarship and Professional Work - Business. 297.
https://digitalcommons.butler.edu/cob_papers/297
