This model uses an ensemble of multiple algorithms for better accuracy but slower training.
Metric | Value |
---|---|
Accuracy | 82.03% |
Precision | 82.53% |
Recall | 82.03% |
F1 Score | 82.11% |
# | Model | Accuracy | Precision | Recall | F1 Score |
---|---|---|---|---|---|
1 | RandomForestClassifier | 61.27% | 71.15% | 61.27% | 63.10% |
2 | GradientBoostingClassifier | 81.78% | 82.52% | 81.78% | 81.89% |
3 | LogisticRegression | 79.05% | 79.69% | 79.05% | 79.26% |
Date | Type | Accuracy | F1 Score |
---|---|---|---|
2025-07-07 09:36:56 (Current) | ensemble | 82.03% | 82.11% |
2025-07-06 23:34:43 | ensemble | 82.03% | 82.11% |
2025-07-06 19:11:12 | ensemble | 82.03% | 82.11% |
2025-07-06 16:39:25 | ensemble | 82.03% | 82.11% |
2025-07-05 16:09:18 | ensemble | 82.03% | 82.11% |
Category | Accuracy |
---|---|
Legal & Professional Services | 96.77% |
Personal Care & Grooming | 95.29% |
Leisure & Entertainment | 94.38% |
Shopping | 93.55% |
Health & Fitness | 92.86% |
Category | Accuracy |
---|---|
Travel & Vacation | 86.96% |
Education & Learning | 86.32% |
Transportation | 85.37% |
Gifts & Donations | 84.88% |
Pets & Animal Care | 83.72% |