Interpretability has drawn increasing attention in machine learning. Partially linear additive models provide an attractive middle ground between the simplicity of generalized linear model and the ...

Instrumental variable (IV) methods are popular in non-experimental studies to estimate the causal effects of medical interventions. These approaches allow for the consistent estimation of treatment ...

While machine learning and deep learning models often produce good classifications and predictions, they are almost never perfect. Models almost always have some percentage of false positive and false ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...