Estimation of the Conditional Probability Using a Stochastic Gradient Process
Ali Labriji,
Abdelkrim Bennar,
Mostafa Rachik and
Barbara Martinucci
Journal of Mathematics, 2021, vol. 2021, 1-7
Abstract:
The use of conditional probabilities has gained in popularity in various fields such as medicine, finance, and imaging processing. This has occurred especially with the availability of large datasets that allow us to extract the full potential of the available estimation algorithms. Nevertheless, such a large volume of data is often accompanied by a significant need for computational capacity as well as a consequent compilation time. In this article, we propose a low-cost estimation method: we first demonstrate analytically the convergence of our method to the desired probability and then we perform a simulation to support our point.
Date: 2021
References: Add references at CitEc
Citations:
Downloads: (external link)
http://downloads.hindawi.com/journals/jmath/2021/7660113.pdf (application/pdf)
http://downloads.hindawi.com/journals/jmath/2021/7660113.xml (application/xml)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hin:jjmath:7660113
DOI: 10.1155/2021/7660113
Access Statistics for this article
More articles in Journal of Mathematics from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().