Cloud Based Error Correction and Big Data Mining for Computer Machine Learning Algorithms

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.

Publication Details

Journal
Journal of Electronics and Information Science
Published
2025-01-01
DOI
https://doi.org/10.23977/jeis.2025.100119
Primary Topic
Data Mining Algorithms and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Cloud Based Error Correction and Big Data Mining for Computer Machine Learning Algorithms

Journal of Electronics and Information Science
Data Mining Algorithms and Applications
article

Cloud Based Error Correction and Big Data Mining for Computer Machine Learning Algorithms

article en

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.

Journal of Electronics and Information ScienceVol. 10(1)
Openalex Percentile: Top 80%
Data Mining Algorithms and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Cloud Based Error Correction and Big Data Mining for Computer Machine Learning Algorithms · Journal of Electronics and Information Science (2025) | TGRS Research Map | TGRS