Research map / Label-efficient and robust learning / Recognition and long-tail
Learning Deep Representation from Big and Heterogeneous Data for Traffic Accident Inference
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| stacked denoising autoencoder features instead of decision tree on raw mobility | accident risk prediction · Japan traffic accident risk | MAE: 1.18 -> 0.96 | Helped |
| SdAE vs logistic regression | accident risk prediction · Japan traffic accident risk | MRE: 0.40 -> 0.39 | No clear effect |
| SdAE vs SVM | accident risk prediction · Japan traffic accident risk | RMSE: 1.73 -> 1.00 | Helped |
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