pumml
Positive and Unlabeled Materials Machine Learning (pumml) is a code that uses semi-supervised machine learning to classify materials from only positive and unlabeled examples.
Positive and Unlabeled Materials Machine Learning (pumml) is a code that uses semi-supervised machine learning to classify materials from only positive and unlabeled examples.
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Positive and Unlabeled Materials Machine Learning (pumml) is a code that uses semi-supervised positive and unlabeled (PU) machine learning to classify materials when data is incomplete and only examples of "positive" materials are available. As an example, pumml was used to predict the "synthesizability" of bulk and 2D materials from "positive" examples of synthesized materials.
Summary
Positive and Unlabeled Materials Machine Learning (pumml) is a code that uses semi-supervised machine learning to classify materials from only positive and unlabeled examples.
Last Updated
Oct 26, 2021 at 16:54
License
MIT
Total Downloads
2.7K
Supported Platforms
GitHub Repository
https://github.com/ncfrey/pummlDocumentation
https://pumml.readthedocs.io/