Research map / Probabilistic and scientific modeling / Variational and generative sampling
Pairwise Choice Markov Chains
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use PCMC instead of MNL on SFwork | Discrete choice model · SFwork | prediction error (l1): 36.2% error reduction | Helped |
| Use PCMC instead of MNL on SFshop | Discrete choice model · SFshop | prediction error (l1): 46.5% error reduction | Helped |
| Use PCMC instead of MMNL on SFwork | Discrete choice model · SFwork | prediction error (l1): 24.4% error reduction | Helped |
| Use PCMC instead of MMNL on SFshop | Discrete choice model · SFshop | prediction error (l1): 31.7% error reduction | Helped |
| Train on 75% of SFwork data, PCMC vs MNL | Discrete choice model · SFwork | prediction error (l1): 35.9% reduction | Helped |
| Train on 75% of SFwork data, PCMC vs MMNL | Discrete choice model · SFwork | prediction error (l1): 24.5% reduction | Helped |
| Give MMNL more parameters than PCMC (k mixtures chosen accordingly) | MMNL · SFwork/SFshop | prediction error (l1) | Hurt |
| Increase proportion of training data | PCMC · SFwork | prediction error (l1) | Helped |
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