Table 6 Baseline model compiled in this paper.
Researcher | Selected algorithm/method | Baseline model | Characteristics of baseline model |
|---|---|---|---|
Abdurashidova et al. (2023) | Digital education model | SVM (Support Vector Machine) model | Efficient processing of small-scale data, supporting classification and regression. |
Zheng et al. (2023) | Deep belief network | KNN (K-Nearest Neighbors) model | Simple classification model based on distance, easy to explain. |
Badal and Sungkur (2023) | RF classifier | DT (Decision Tree) model | Single tree structure, suitable for dealing with classification problems |
Grajeda et al. (2024) | Multi-agent learning model | GCN (Graph Convolutional Network) model | Static graph structure, suitable for processing simple graph data. |
Yuan et al. (2024) | Graph automatic encoder | GAT (Graph Attention Network model | Dynamically capture the feature weights of neighbor nodes, which is suitable for complex dependency modeling. |
