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leschultz/materials_application_domain_machine_learning
leschultz/materials_application_domain_machine_learning PublicA package for definining the domain of a machine learning model via a feature dissimilarity metric.
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Skunkworks-Uncertainty-Quantification
Skunkworks-Uncertainty-Quantification PublicPre-clustering superconductors dataset with HDBSCAN, sampling with randomized presorted clusters, then using Mahalanobis distance as an uncertainty quantification metric with R^2.
Jupyter Notebook
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LightGBM-binary-classification-example
LightGBM-binary-classification-example PublicA model that predicts the default rate of credit card holders using the LightGBM classifier. Trained the LightGBM classifier with Scikit-learn's GridSearchCV.
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