Teaching Design of Mathematics Application Based on Naive Bayes
Huanzhang Ling and
Hangjun Che
Mathematical Problems in Engineering, 2022, vol. 2022, 1-6
Abstract:
There is a huge amount of mathematical information in the world, and mathematics is everywhere and nowhere. Bayesian theory is based on a process of statistical inference that requires the calculation of general and prior information to obtain a posteriori information. Its main features are the use of probabilities to represent all forms of uncertainty and the use of probabilistic rules to enable learning and inference, estimating the probability of future occurrences by calculating the probability of a past time. In order to bring mathematics closer to life, this paper explores the teaching of mathematical applications in terms of material selection, teaching arrangement, and professional integration. At the same time, in order to better realize mathematics application teaching, effectively improve the classroom effect of mathematics application teaching, and make students better accept mathematical knowledge and apply it to practical applications, the design of mathematics application teaching in this paper is also based on Naive Bayes.
Date: 2022
References: Add references at CitEc
Citations:
Downloads: (external link)
http://downloads.hindawi.com/journals/mpe/2022/7244001.pdf (application/pdf)
http://downloads.hindawi.com/journals/mpe/2022/7244001.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:jnlmpe:7244001
DOI: 10.1155/2022/7244001
Access Statistics for this article
More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().