Year: 2025
Type: article
Abstract: With the advent of the Big Data (BD) era, Machine Learning (ML) algorithms have been widely applied in various industries. Among them, ML algorithms are mainly trained on computers. Due to various problems that may arise during the training process, ML algorithms produce various errors and cannot achieve good results. This article analyzed a cloud based error correction system and BD mining system for computer ML algorithms. This system could effectively solve various problems that arose in ML algorithms, and its effectiveness was verified through experiments. By analyzing cloud error correction technology and BD mining technology, a cloud error correction system and BD mining system were constructed, and ML algorithms were used to verify the feasibility of the system in terms of average running time and accuracy. Through experimental research, it was found that the accuracy of using ML algorithms was 5.8% higher than using neural network algorithms. There were currently multiple ways to process BD, and using ML patterns to optimize BD processing was a relatively effective approach. Simulation experiments showed that the ML algorithm proposed in this paper had higher accuracy overall than neural network algorithms, thus making it an effective and practical optimization algorithm.
Author: Ziyi Huang
Institution: Criminal Investigation Police University of China
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $329
OpenAlex ID: W4411355655