Research map / Probabilistic and scientific modeling / Uncertainty and Gaussian processes
Heterogeneous Multi-output Gaussian Process Prediction
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Jointly model the heterogeneous outputs with HetMOGP instead of independent ChainedGP outputs | Behavior dataset · Behavior dataset, Global | NLPD (× 10⁻²): 14.91 ± 1.05 -> 13.74 ± 0.41 | Helped |
| Jointly model the heterogeneous outputs with HetMOGP instead of independent ChainedGP outputs | Behavior dataset · Behavior dataset, Bernoulli output 2 | NLPD (× 10⁻²): 5.19 ± 0.81 -> 5.41 ± 0.05 | Mixed |
| Jointly model the heterogeneous outputs with HetMOGP instead of independent ChainedGP outputs | London dataset · London dataset, Global | NLPD (× 10⁻²): 17.31 ± 1.06 -> 16.44 ± 0.01 | Helped |
| Use information from the real-valued output to predict the binary output | HetMOGP · Missing Gap Prediction, binary output | NLPD (× 10⁻²): 40.51 ± 0.08 × 10⁻² -> 32.5 ± 0.2 × 10⁻² | Helped |
| Jointly model gender and logarithmic age instead of predicting outputs independently | HetMOGP · Arrhythmia, gender and logarithmic age | NLPD: 0.0191 vs 0.0191 | No clear effect |
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