RT Journal Article
T1 Award Price Estimator for Public Procurement Auctions Using Machine Learning Algorithms: 												Case Study with Tenders from Spain
A1 Rodriguez, Manuel J.Garcia
A1 Montequin, Vicente Rodriguez
A1 Aranguren Ubierna, Andoni
A1 Hermida, Roberto Santana
A1 Araujo, Basilio Sierra
A1 Jauregi, Ana Zelaia
AB The public procurement process plays an important role in the efficient use of public resources. In this context, the evaluation of machine learning techniques that are able to predict the award price is a relevant research topic. In this paper, the suitability of a representative set of machine learning algorithms is evaluated for this problem. The traditional regression methods, such as linear regression and random forest, are compared with the less investigated paradigms, such as isotonic regression and popular artificial neural network models. Extensive experiments are conducted based on the Spanish public procurement announcements (tenders) dataset and employ diverse error metrics and implementations in WEKA and Tensorflow 2.
SN 1220-1766
YR 2021
FD 2021
LK https://hdl.handle.net/11556/3303
UL https://hdl.handle.net/11556/3303
LA eng
NO Rodriguez , M J G , Montequin , V R , Aranguren Ubierna , A , Hermida , R S , Araujo , B S & Jauregi , A Z 2021 , ' Award Price Estimator for Public Procurement Auctions Using Machine Learning Algorithms : Case Study with Tenders from Spain ' , Studies in Informatics and Control , vol. 30 , no. 4 , pp. 67-76 . https://doi.org/10.24846/V30I4Y202106
NO Publisher Copyright: © 2021. All Rights Reserved.
DS TECNALIA Publications
RD 28 jul 2024