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#1 Federal

Code for Predicting MIEs from Gene Expression and Chemical Target Labels with Machine Learning (MIEML)

Organization: U.S. Environmental Protection Agency
Dataset Last Updated: March 02, 2022

Modeling data and analysis scripts generated during the current study are available in the github repository: https://github.com/USEPA/CompTox-MIEML. RefChemDB is available for download as...

FILE

Search relevance: 1.00 | Views last month: 2 | Catalog Last Checked: September 10, 2026 at 06:58 PM

#2 Federal

Contingency: a python library for fast, vectorized metrology with binary contingency counts.

Organization: National Institute of Standards and Technology
Dataset Last Updated: March 19, 2026

With this tool, users can rapidly calculate binary classifier metrics like Matthew's Correlation Coefficient, F-Scores, and Average Precision Scores from scalar and binary predictions. It is...

GIT
WEB

Search relevance: 1.00 | Views last month: 0 | Catalog Last Checked: September 10, 2026 at 05:53 PM

#3 Federal

Contingency: a python library for fast, vectorized metrology with binary contingency counts.

Organization: Department of Commerce
Dataset Last Updated: March 19, 2026

With this tool, users can rapidly calculate binary classifier metrics like Matthew's Correlation Coefficient, F-Scores, and Average Precision Scores from scalar and binary predictions. It is...

GIT
WEB

Search relevance: 1.00 | Views last month: 0 | Catalog Last Checked: October 02, 2026 at 07:54 PM

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Code for Predicting MIEs from Gene Expression and Chemical Target Labels with Machine Learning (MIEML)

Contingency: a python library for fast, vectorized metrology with binary contingency counts.

Contingency: a python library for fast, vectorized metrology with binary contingency counts.