AutoRA Divergence Experimentalist
The divergence experimentalist identifies experimental conditions $\vec{x}' \in X'$ with respect the distance between existing experimental data $\vec{x}, $\vec{y} and data predicted by a model $\vec{x_pool}, $\vec{y_pred}:
$$ \underset{\vec{x}'}{\arg\max}~sum(d((\vec{x}, \vec{y}), (\vec{x_pool}, \vec{y_pred})) $$
The aim of this experimentalist is to combine novelty and uncertainty by using a distance that combines both: The distance between existing conditions to new conditions and the distance of existing observations to predictions.
Metadata
Release files for autora-experimentalist-divergence 0.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| autora_experimentalist_divergence-0.0.2.tar.gz | 11.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| autora_experimentalist_divergence-0.0.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 16.9 kB
Release files / autora_experimentalist_divergence-0.0.2.tar.gz
| Download URL | autora_experimentalist_divergence-0.0.2.tar.gz |
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| Size | 11.3 kB |
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Release files / autora_experimentalist_divergence-0.0.2-py3-none-any.whl
| Download URL | autora_experimentalist_divergence-0.0.2-py3-none-any.whl |
|---|---|
| Size | 5.6 kB |
| Tags | Python 3 |
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