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Structural Optimization of Causal Driven Model Based on Bayesian Network in High-dimensional Data Classification

Kuo Li

Kuo Li

  • College of Computer Science and Technology, Jilin UniversityChangchun, China
  • Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin UniversityChangchun, China
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Li, Kuo
, 
Aimin Wang

Aimin Wang

  • College of Computer Science and Technology, Jilin UniversityChangchun, China
  • Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin UniversityChangchun, China
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Wang, Aimin
, 
Limin Wang

Limin Wang

  • College of Computer Science and Technology, Jilin UniversityChangchun, China
  • Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin UniversityChangchun, China
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Wang, Limin
, 
Yuetan Zhao

Yuetan Zhao

  • College of Computer Science and Technology, Jilin UniversityChangchun, China
  • Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin UniversityChangchun, China
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Zhao, Yuetan
 and 
Xinyu Zhu

Xinyu Zhu

College of Software, Jilin UniversityChangchun, China
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Zhu, Xinyu
  
Feb 27, 2025
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Published Online: Feb 27, 2025
Received: Oct 09, 2024
Accepted: Jan 18, 2025
DOI: https://doi.org/10.2478/amns-2025-0152
Keywords
© 2025 Kuo Li et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Figure 1.

BLS framework
BLS framework

Figure 2.

Broad-BNN model structure with dynamic structural mapping units
Broad-BNN model structure with dynamic structural mapping units

Figure 3.

Comparison of classification accuracy
Comparison of classification accuracy

Figure 4.

Comparison of task time consumption
Comparison of task time consumption

Figure 5.

Comparison of recall rates
Comparison of recall rates

Figure 6.

Comparison of F1 values
Comparison of F1 values

Figure 7.

RMSE comparison
RMSE comparison

Figure 8.

Comparison of classification precision
Comparison of classification precision
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