Research and Application of User Behavior Data Analysis Technology for E-commerce
, y
27 feb 2025
Acerca de este artículo
Publicado en línea: 27 feb 2025
Recibido: 25 sept 2024
Aceptado: 23 ene 2025
DOI: https://doi.org/10.2478/amns-2025-0116
Palabras clave
© 2025 Xiaohan Yuan et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

Figure 7.

Figure 8.

Figure 9.

Figure 10.

Comparison of effects of three models
Model Name | Accuracy rate | Recall rate | F1 Value |
---|---|---|---|
Logistic regression | 4.25% | 4.31% | 4.27% |
LightGBM | 5.61% | 5.63% | 5.62% |
LightGBM + LR | 5.81% | 602.70% | 5.93% |
Evaluation indicators of each algorithm
Precision | Coverage | MAE | Diversity | Surprise | Unexpectedness | |
---|---|---|---|---|---|---|
16.68% | 8.34% | 89.11% | 0.365 | 10.956 | 8.841 | |
23.94% | 99.20% | 78.68% | 0.914 | 8.130 | 1.633 | |
26.40% | 99.20% | 76.93% | 0.936 | 8.242 | 1.444 |
Overall prediction results
Model Name | Accuracy rate | Recall rate | F1 |
---|---|---|---|
Logistic regression | 4.66% | 4.72% | 4.68% |