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Multi-Type Urban Crime Prediction
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Jointly model cross-type and spatio-temporal correlations | Crime prediction with CCC · NYC, 1-day prediction | RMSE: 0.255 -> 0.223 | Helped |
| Jointly model cross-type and spatio-temporal correlations | Crime prediction with CCC · NYC, 7-day prediction | RMSE: 0.360 -> 0.330 | Helped |
| Jointly model cross-type and spatio-temporal correlations | Crime prediction with CCC · NYC, 1-day prediction | MAE: 0.029 -> 0.021 | Helped |
| Jointly model cross-type and spatio-temporal correlations | Crime prediction with CCC · NYC, 7-day prediction | MAE: 0.042 -> 0.033 | Helped |
| Add cross-type correlation modeling (ablation) | CCC crime prediction · NYC, 1-day and 7-day prediction | RMSE | Helped |
| Add intra-region temporal correlation modeling (ablation) | CCC crime prediction · NYC, 1-day and 7-day prediction | RMSE | Helped |
| Add inter-region spatial correlation modeling (ablation) | CCC crime prediction · NYC, 1-day and 7-day prediction | RMSE | Helped |
| Add shared weight vectors for common features across crime types (ablation) | CCC crime prediction · NYC, 1-day and 7-day prediction | RMSE | Helped |
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