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Teaching Design of Mathematics Application Based on Naive Bayes

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  • Huanzhang Ling
  • Hangjun Che

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.

Suggested Citation

  • Huanzhang Ling & Hangjun Che, 2022. "Teaching Design of Mathematics Application Based on Naive Bayes," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-6, June.
    • Handle: RePEc:hin:jnlmpe:7244001
    DOI: 10.1155/2022/7244001
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