Missing data are a major hindrance to statistical analysis because standard methods require the missing values to be imputed first. AMELIA and MICE fiare two popular imputation methods, but their ...

Sparse data can impact the effectiveness of machine learning models. As students and experts alike experiment with diverse datasets, sparse data poses a challenge. The Leeds Master’s in Business ...

Behavioral variability is quietly sabotaging clinical trials—but it doesn't have to. Here's how predictive behavioral modeling can improve trial design, reduce dropout, and deliver more inclusive, ...

There are data about practically everything these days, and they can be used to try to answer any number of questions. Do clinical trials really show a drug works? Can surveys really signal who’s ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.