A framework to conduct selective inference for Co-Regularization Enhances Knowledge Transfer (CoRT)
Project description
CoRT-SI: Selective Inference For Co-Regularization Transfer (CoRT)
CoRT-SI is a Python package designed for conducting valid statistical inference for CoRT. It implements selective inference methods to control the false positive rate (FPR) while maximizing the true positive rate (TPR) in feature selection after transfer learning.
Requirements & Installation
This package has the following requirements:
numpympmathscikit-learn
This package can be installed using pip:
pip install cort-si
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