Can I read Logistic Regression vs. Random Forest Fairness on EtoBox?

Logistic Regression vs. Random Forest Fairness by Priyanka Kilaniya is a document available to read on EtoBox.

What is Logistic Regression vs. Random Forest Fairness about?

This paper compares logistic regression and random forest models in terms of individual fairness in machine learning applications, particularly in high-stakes domains like finance and criminal justice. The findings indicate that while random forests provide slightly higher accuracy, logistic regression offers better individual consistency and interpretability, making it more suitable for fairness-sensitive contexts. The study emphasizes the importance of model selection in achieving ethically responsible AI

Author

Priyanka Kilaniya

Language

EN