Title: Influence of technology optimisation based on machine learning algorithm on financial management innovation of e-commerce enterprises

Authors: Rui Min

Addresses: School of Economics and Management, Jiangsu Maritime Institute, Nanjing, 210000, China

Abstract: In order to improve the financial ability of e-commerce enterprises to deal with risks and optimise their financial early warning effect, a complete random forest-based financial early warning method for e-commerce enterprises based on k-nearest neighbours is proposed. Firstly, in order to improve the classification effect of complete random forest algorithm on dynamic data, a complete random forest algorithm based on k-nearest neighbour is proposed; then, on this basis, the financial risk evaluation system of e-commerce enterprises is established by using the analytic hierarchy process, so as to complete the construction of the financial early warning model of e-commerce enterprises; and finally its application effect is tested and analysed. The results show that the minimum prediction accuracy and F1 value of the model remain at 0.7, which are 0.58 and 0.3 higher than the NB model, respectively.

Keywords: k-nearest neighbour; KNN; random forest; machine learning; e-commerce; corporate finance.

DOI: 10.1504/IJCSYSE.2023.132911

International Journal of Computational Systems Engineering, 2023 Vol.7 No.2/3/4, pp.124 - 134

Received: 01 Nov 2022
Accepted: 01 Mar 2023
Published online: 16 Aug 2023 *

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