Abstract
Aiming at the problem of the association data mining in the big data environment, this paper proposes a method of the association data mining based on the mathematical model of the partial calculus classification. Experiments show that this method improves the efficiency and accuracy of the data mining, and achieves satisfactory results. Due to the large amount of the data and the multi-dimensional characteristics of the database, the traditional mining methods cannot build the accurate mathematical models when processing the data, which is prone to some problems such as the loss of information and the hard partition. Therefore, the application of the financial mathematical model mining technology based on the partial differential calculus is very prominent.
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Acknowledgment
Foundation Project: 2017 Ningxia University Science Research Project (Project Serving Local Economic and Social Development); Project Number: NGY2017181; Project Name: Research on Incentive Mechanism Model of Small and Medium-sized Enterprises in Ningnan Mountain Areas Based on the Fuzzy Comprehensive Evaluation Method; Key Subprojects of Undergraduate Teaching Project in Higher Education in 2017; Project Name: Exploration and practice of the information construction of Probability Theory & Mathematical Statistics under the concept of the CDIO education.
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Ma, S. (2019). Research on the Mining Technology of the Financial Mathematical Model Based on the Partial Differential Calculus. In: Sugumaran, V., Xu, Z., P., S., Zhou, H. (eds) Application of Intelligent Systems in Multi-modal Information Analytics. MMIA 2019. Advances in Intelligent Systems and Computing, vol 929. Springer, Cham. https://doi.org/10.1007/978-3-030-15740-1_26
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DOI: https://doi.org/10.1007/978-3-030-15740-1_26
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