Research and Application of User Behavior Data Analysis Technology for E-commerce
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Feb 27, 2025
About this article
Published Online: Feb 27, 2025
Received: Sep 25, 2024
Accepted: Jan 23, 2025
DOI: https://doi.org/10.2478/amns-2025-0116
Keywords
© 2025 Xiaohan Yuan et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
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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% |