Parker will create statistical methods for machine learning models that are specifically designed to account for survey design, the unique way in which data is collected. He aims to take advantage of ...

Our findings suggest that integrating machine learning into traditional statistical methods can provide more accurate and generalizable models for disease risk prediction.

Understanding these assumptions is essential for ensuring the accuracy and reliability of statistical analyses across various fields, from economics to machine learning [2] [3].

In “Hierarchical confounder discovery in the experiment–machine learning cycle,” published in Cell Patterns, the authors define a new nonparametric statistical method for scoring the effect ...

Students gave their consent that their stories could be used for research purposes and might be published. Out of a class of ...

A new study presents a machine learning model that accurately predicts the compressive strength of high-strength concrete, ...

The natural protein universe is vast, and yet, going beyond and designing new proteins not observed in nature can yield new ...