Build using:
swift build
Example run:
swift run -c release NoisyLabelsExperiments run \
--dataset weather-sentiment \
--train-data-portion 0.9 \
--synthetic-predictors-count 16 \
--use-synthetic-predictor-features \
--results-dir temp/results-synthetic
For medical-causes
and medical-treats
we are using LIA
configured with the following options:
- Predictor Embedding Size:
32
- Instance Hidden Unit Counts:
[32, 32, 32, 32]
- Predictor Hidden Unit Counts:
[]
- Confusion Latent Size:
1
- Gamma:
0.0
- Entropy Weight:
0.0
- Use Soft Predictions:
true
- Learning Rate:
1e-4
- Learning Rate Decay Factor:
1.0
- Batch Size:
512
- M Step Count:
1000
- EM Step Count:
2
- Marginal Step Count:
1000