On a machine learning based analysis of online transaction

Kailai Chen

doi:10.1117/12.2675229

25 May 2023 On a machine learning based analysis of online transaction

Kailai Chen

Proceedings Volume 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022); 1263603 (2023) https://doi.org/10.1117/12.2675229
Event: Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 2022, Shenyang, China

Abstract

With the rapid development of computer science and artificial intelligence, machine learning as a main method to realize artificial intelligence has developed in many fields. The purpose of this paper is to use the unsupervised algorithm of machine learning to solve the real business problem of online transactions. The traditional statistical method is replaced by machine learning method to analyze the shopping behaviors and preferences of different customers, so as to get more accurate results. The paper processed 541909 sets of original online transaction data with various technologies of data preprocessing (ETL), and used the PCA algorithm and feature selection methods to reduce data dimensions, which could yield different results due to the strengths and drawbacks of each method. The paper used the K-Means algorithm, implemented by Python, to cluster the data after dimension reduction, visualized the data sets, and drew conclusions. The experimental results demonstrate that the proposed method is effective.

Citation Download Citation

Kailai Chen "On a machine learning based analysis of online transaction", Proc. SPIE 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 1263603 (25 May 2023); https://doi.org/10.1117/12.2675229

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available