Ultimately, we employed decision trees, logistic regression, and random forests to reach our objective. Of these, random forest yielded the highest accuracy of 96%, making them useful for obtaining ...

Logistic regression recognizes and accounts for different base rates, but it does so implicitly through the data and the model’s estimation process rather than requiring explicit input of base ...

The sslearn library is a Python package for machine learning over Semi-supervised datasets. It is an extension of scikit-learn.

For each participant, we find the value of δ that minimizes the deviance of a logistic regression model that uses the d-values ... In contrast, our approach to identify changes in value does not ...