Applicability domains for cheminformactics.
Project description
MLChemAD
Applicability domain definitions for cheminformatics modelling.
Getting Started
Install
pip install mlchemad
Example Usage
from mlchemad import TopKatApplicabilityDomain, data
# Create the applicability domain
app_domain = TopKatApplicabilityDomain()
# Fit it to the training set
app_domain.fit(data.training)
# Determine outliers from multiple samples (rows) ...
print(app_domain.contains(data.test))
# ... or a unique sample
print(app_domain.contains(data.test[5]))
Depending on the definition of the applicability domain, some samples of the training set might be outliers themselves.
Applicability domains
The applicability domain defined by MLChemAD as the following:
- Bounding Box
- PCA Bounding Box
- Convex Hull (does not scale well)
- TOPKAT's Optimum Prediction Space (recommended)
- Leverage
- Hotelling T²
- Distance to Centroids
- k-Nearest Neighbors
- Isolation Forests
- Non-parametric Kernel Densities
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