Machine learning is a powerful tool for solving problems that involve a lot of data. It is being used in many different fields. The first step in creating a machine learning system is to understand what you want to achieve and then turn that goal into a plan for using machine learning. This is called problem formulation. Problem formulation is important because it not only helps you understand what you want to achieve but also helps you figure out if you have the right data to make it work. Practitioners need to try different approaches and see what works best for their data. This can take some trial and error. This study looks at a new tool designed to make problem formulation easier and see if it helps practitioners.
Thank you for your interest, but this study is recruiting by invitation only.
North Carolina (Statewide)
Yue Wang
School of Information and Library Science
Behavioral or Social
Observational
Healthy Volunteer or General Population
23-0406