This project explores Logistic Regression applied to the Diabetes dataset, using both R and Python. The purpose is to compare results and learn how different tools handle the same statistical analysis ...

Official Code for Learning to Scale Logits for Temperature-conditional GFlowNets (ICML 2024) - dbsxodud-11/logit-gfn ...

The data doctor continues his exploration of Python-based machine learning techniques, explaining binary classification using logistic regression, which he likes for its simplicity.

The data doctor continues his exploration of Python-based machine learning techniques, explaining binary classification using logistic regression, which he likes for its simplicity.

The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to ...

We explain the theoretical and econometric underpinnings of mixed logit and demonstrate its empirical usefulness in the context of a specific but topical area of accounting research: financial ...

American Journal of Agricultural Economics, Vol. 85, No. 1 (Feb., 2003), pp. 248-253 (6 pages) Substantive income effects are incorporated in a logit or nested-logit model by assuming that utility is ...